NCHRP Project Planning and Preliminary Engineering Applications Guide to the HCM

Transcription

1 NCHRP Project Planning and Preliminary Engineering Applications Guide to the HCM Copy No. Second Draft Guide Prepared for: National Cooperative Highway Research Program Transportation Research Board National Research Council Transportation Research Board NAS-NRC LIMITED USE DOCUMENT This report, not released for publication, is furnished only for to members of, or participants in the work of, the National Cooperative Highway Research Program. It is to be regarded as fully privileged, and disse mination of the information included herein must be approved by the NCHRP. December, 2014 Dr. Richard Dowling, Paul Ryus, Kittelson & Associates, Inc. Dr. Bastian Schroeder, ITRE at North Carolina State University Dr. F. Thomas Creasey, Stantec; Dr. Michael Kyte, University of Idaho; Danica Rhoades, Write Rhetoric 1

2 Table of Contents List of Exhibits... 7 PART I INTRODUCTION Chapter 1 Introduction Purpose Target Audience How to Use the Guide Organization Scope Levels of Analysis The Hierarchy of Analysis Methods Chapter 2 Mid-Level (Facility Specific) Analyses Project Traffic And Environmental Impact Studies Using Defaults to Reduce Data Needs References Chapter 3 High Level Analyses Screening and Scoping Studies Long and Short Range Area-wide Transportation Planning System Performance Monitoring References Chapter 4 Working with Traffic Demand Data Overview Selection of an Analysis hour Converting Daily Volumes to Shorter Timeframes Seasonal Adjustments to Traffic Volumes Rounding Traffic Volumes Differences Between Observed Volumes and Actual Demand Constraining Demand for Upstream Bottleneck Metering Generating Turning Movement Volume Estimates from Link Volumes References Chapter 5 Predicting Intersection Traffic Control Overview

3 2. Manual on Uniform Traffic Control Devices Predicting Future Intersection Traffic Control References Chapter 6 Default Values to Reduce data Needs Overview When to Consider Default Values Sources of Default Values Developing Local Default Values References Chapter 7 Service volume Tables to Reduce Analysis Effort PART II MID-LEVEL ANALYSIS METHODS Chapter 8 Freeway Analyses Introduction Applications Analysis Methods Overview Scoping and Screening Method Employing the HCM with Defaults Simplified HCM Facility Method Reliability Adaptations for advanced Freeway Management Practices Multimodal LOS Example References Chapter 9 Multilane Highways Introduction Applications Analysis Methods Overview Scoping and Screening Method Section Analysis Using HCM with Defaults Multilane Facility Analysis Method Reliability (No Method Available) Multimodal LOS

4 9. Example (None Provided) Reference Chapter 10 Two lane Highways Introduction Applications Analysis Methods Overview Scoping and Screening Section Analysis Using HCM with Defaults Two lane Facility Analysis Method Reliability (No Method Available) Multimodal LOS Example (None Provided) Reference Chapter 11 Urban Streets Introduction Applications Analysis Methods Overview Scoping and Screening Employing the HCM Method With Defaults Simplified HCM Facility Analysis Method Reliability Analysis Multimodal LOS Example References Chapter 12 Signalized Intersections Introduction Applications Analysis Methods Overview SImplified Method Part 1 - V/C CAlculation Simplified Delay, Queue and LOS Calculation Worksheets Reliability Analysis

5 8. Multimodal LOS Example References Chapter 13 Stop Controlled Intersections Overview Applications Analysis Methods Overview Simplified HCM Method for All-Way Stop-Controlled Intersections Simplified HCM Method for Two-Way Stop-Controlled Intersection Level of Service Analysis (AWSC and TWSC) Queuing Analysis (AWSC and TWSC) Worksheets Reliability Analysis Multimodal LOS (No Method Available) Example (None Provided) References Chapter 14 Roundabout Intersections Overview Applications Analysis Methods Overview Simplified HCM Method Worksheets Reliability Analysis Multimodal LOS (No Method Available) Example (None Provided) References Chapter 15 Pedestrians, Bicyclists, and Public Transit Overview Freeways Multilane and Two-Lane Highways Urban Streets Signalized Intersections

6 6. Stop-Controlled Intersections Roundabouts Interchange Ramp Terminals Off-Street Pathways References Chapter 16 Truck Level of Service The Truck Level of Service Index Estimation of On-Time Arrival from TTI A Service-TTI Lookup Table for Truck LOS References PART III HIGH LEVEL ANALYSES Chapter 17 Corridor Quick estimation Screenline Analysis Introduction Screening for Capacity and Multimodal LOS Hot Spots Chapter 18 Areas and Systems Overview Computational Tools Data Needs Estimation of Demand Model Inputs Performance Measure Estimation References PART IV CASE STUDIES I. Freeway Master Plan II. Bus Rapid transit on an Urban Street III. Long-Range CountyWide Transportation Plan IV. Roadway System Monitoring

7 LIST OF EXHIBITS Exhibit 1: Scope of the Planning and Preliminary Engineering Applications Guide Exhibit 2: Relative Effort and Precision of Traffic Performance Estimation Methods Exhibit 3: Project Impact Analysis Task Cross Reference Table Exhibit 4: Screening and Scoping Task Cross Reference Table Exhibit 5: Areawide Planning Analysis Task Cross Reference Table Exhibit 6: Performance Monitoring Task Cross Reference Table Exhibit 7: Illustrative K 30 Values Exhibit 8: Illustrative D-Factor Values Exhibit 9: Capacity Constraining Demands Entering and Within HCM Study Facility Exhibit 10: Origin-Destination Labels for Intersection Turning Movements Exhibit 11: Required Data for MUTCD Warrant Analysis Exhibit 12: Intersection Control Type by Peak Hour Volume Exhibit 13: Analysis Options for Freeways Exhibit 14: Daily and Peak Hour Service Volume and Capacity Table for Freeways Exhibit 15: Required Data for HCM Freeway Analysis Exhibit 16: Schematic of HCM Segment to Simplified HCM Method Section Exhibit 17: Required Data for Simplified Freeway Facility Analysis Exhibit 18: Values for the Parameters of Equation Exhibit 19: LOS Criteria for Freeway Facilities Exhibit 20: Characterizing Travel Time Reliability Exhibit 21: Input Data Needs for HCM Reliability Analysis of Freeways Exhibit 22: Analysis Options for Multilane Highways Exhibit 23: Daily and Peak Hour Service Volume and Capacity Table for Multilane Highway Sections72 Exhibit 24: Required Data for Multilane Highway Section Analysis Exhibit 25: Controlled Intersections and Sections on Highway Facility Exhibit 26: Parameters for Multilane Highway Speed Estimation

8 Exhibit 27: Queue Density Thresholds for Multi-Lane Highways Exhibit 28: Analysis Options for Two-lane Highways Exhibit 29: Daily and Peak Hour Service Volume and Capacity Table for Two Lane Highway Sections82 Exhibit 30: Required Data for Two lane Highway Section Analysis Exhibit 31: Auto Level of Service Criteria for Two Lane Highway Sections Exhibit 32: Controlled Intersections and Sections on Highway Facility Exhibit 33: No-Passing Adjustment for Two-Lane Highway Speed Estimation Exhibit 34: Relationships between Urban Street Facility, Urban Street Segment, and Intersections. 92 Exhibit 35: Analysis Options for Urban Streets Exhibit 36: Service Volume Table for Urban Streets (AADT and Peak Hour) Exhibit 37: Signal Approach Operating Characteristics for Given Arterial LOS Thresholds Exhibit 38: Signal Approach Through Capacities Exhibit 39: Required Data for Urban Street Analysis Exhibit 40: Simplified Urban Street Analysis Method Steps Exhibit 41. Progression Factor Exhibit 42: Simplified Urban Street Method Worksheets Exhibit 43: Overflow Delay When Demand Exceeds Capacity over the Analysis Period Exhibit 44: Delay Resulting When Demand Is Less than Capacity over the Analysis Period Exhibit 45: Urban Street Segment Planning Method, Oversaturated Conditions, Analysis Framework105 Exhibit 46: Urban Street Segment Planning Method, Oversaturated Conditions Exhibit 47: Queue Accumulation Polygon for Oversaturated Conditions Exhibit 48: Urban Street Segment Planning Method, Oversaturated Conditions Worksheet Exhibit 49: Analysis Options for Signalized Intersections Exhibit 50: Required Data for Signalized Intersection Analysis Exhibit 51: Intersection Capacity Sufficiency Analysis Steps Exhibit 52: Left-Turn Adjustment Factor (E LT ) Exhibit 53: Right-Turn Adjustment Factor (E RT ) Exhibit 54: Parking Adjustment Factor (E p ) Exhibit 55: Lane Utilization Factor (E LU )

9 Exhibit 56: Left-Turn Adjustment Factor (E LT ) Exhibit 57: Intersection Sufficiency Exhibit 58: Signalized Intersection Planning Method, Part II Exhibit 59: Progression Adjustment Factor Exhibit 60: Level of Service, Signalized Intersections Exhibit 61: Signalized Intersection Input Worksheet Exhibit 62: Signalized Intersection Calculations Part I Worksheet Exhibit 63: Signalized Intersection Calculations Part II Worksheet Exhibit 64: Signalized Intersection Calculations Protected/Permitted Left Turn Worksheet Exhibit 65: Example Sensitivity Analysis Table for Signalized Intersection Reliability Exhibit 66: Analysis Options for Stop Controlled Intersections Exhibit 67: Total Entering Capacity for AWSC Intersections Exhibit 68: AWSC Intersection Planning Method, Street 1 Delay, 20% Turns, One-Lane Approaches136 Exhibit 69: AWSC Intersection Planning Method, Street 1 Delay, 20% Turns, Two-Lane Approaches136 Exhibit 70: TWSC Intersection Planning Method, Computational Steps Exhibit 71: Turning Movement Numbering for TWSC Intersection Exhibit 72: Base Critical Headways Exhibit 73: Base Follow Up Headways Exhibit 74: Level of Service - Stop Controlled Intersections Exhibit 75: AWSC Intersection Delay Computation Worksheet Exhibit 76: TWSC Input Data Worksheet Exhibit 77: TWSC Capacity and Delay Computation Worksheet Exhibit 78: Example Sensitivity Analysis Table for Intersection Reliability Exhibit 79: Analysis Options for Stop Controlled Intersections Exhibit 80: Roundabout Planning Method Exhibit 81: Assumed (De Facto) Lane Assignments Exhibit 82: Volume Assignments for Two-Lane Entries Exhibit 83: Capacity Equations for Roundabouts Exhibit 84: Level of Service, Roundabouts

10 Exhibit 85: Roundabout Input Worksheet Exhibit 86: Roundabout V/C and Delay Computation Worksheet Exhibit 87: Example Sensitivity Analysis Table for Intersection Reliability Exhibit 88: Required Data for Multilane and Two-Lane Highway Bicycle Analysis Exhibit 89: Required Data for Urban Street Pedestrian Analysis Exhibit 90: Required Data for Urban Street Bicycle Analysis Exhibit 91: Required Data for Urban Street Transit Analysis Exhibit 92: Efficiency of Multiple Loading Areas at Bus Stops Exhibit 93: Values of Z Associated with Given Failure Rates Exhibit 94: Bus Stop Location Factor Values Exhibit 95: Estimated Bus Running Time Losses on Urban Streets (min/mi) Exhibit 96: Bus Bus Interference Factor Values Exhibit 97: Sensitivity of Bus LOS to Frequency and Speed Exhibit 98: Transit LOS Maximum Auto Volume Table Exhibit 99: Bicycle LOS Maximum Auto Volume Table Exhibit 100: Pedestrian LOS Maximum Auto Volume Table Higher Speed Streets Exhibit 101: Pedestrian LOS Maximum Auto Volume Table Lower Speed Streets Exhibit 102: Required Data for Signalized Intersection Pedestrian Analysis Exhibit 103: Required Data for Signalized Intersection Bicycle Analysis Exhibit 104: Required Data for Two-Way Stop-Controlled Intersection Pedestrian Delay Calculation187 Exhibit 105: Equations for Calculating Probability of Vehicles Yielding to a Crossing Pedestrian Exhibit 106: Required Data for Off-Street Pathway Analysis Exhibit 107: Truck LOS Model Service Measure and Thresholds Exhibit 108: Facility Freight Classification System Exhibit 109: Truck TTI Level of Service Look Up Table Exhibit 110: Example Corridor Screenlines Exhibit 111: Example Corridor Screenlines V/C and LOS Checks Exhibit 112. Required Roadway Segment Data for Area and Roadway Systems Analysis Exhibit 113: Illustrative Look-Up Table of Free-Flow Speed Defaults

11 Exhibit 114: HCM PC Capacities for Freeways Exhibit 115: HCM PC Capacities for Rural Multi-lane Highways Exhibit 116: Illustrative Capacity Per Lane Look-Up Table Exhibit 117: Recommended Speed Flow Equation Parameters Exhibit 118: Example Queuing Diagram Exhibit 119: Speed-Flow Equations Versus HCM 2010 Travel Time Results for Freeway Exhibit 120: Example fit of Speed-Flow Equations to HCM 2010 Speed-Flow Results for Freeway. 218 Exhibit 121: The Smooth and Rough Pipe Analogy for Speed Flow Equations Exhibit 122: Illustrative System LOS Report Typical Weekday Peak Period Exhibit 123. Illustrative System LOS Dashboard Typical Weekday Peak Period

12 PART I INTRODUCTION This part of the Guide provides an overview of the Guide and general information. It describes the different levels of planning and preliminary engineering analyses that may be performed. It provides guidance on adapting demand forecasts for use in Highway Capacity Manual analyses. It provides a method for forecasting future intersection control types, which is a necessary input for most HCM analyses. The chapters in this first part of the Guide also serve as gateways to the remainder of the guide, providing directions on where to find information on the desired analysis methods and examples of their application in case studies. 12

13 CHAPTER 1 INTRODUCTION This Planning & Preliminary Engineering Applications Guide to the Highway Capacity Manual 2010 ( Guide ) is intended to serve as both an educational tool and a reference for practitioners on best practices for applying Highway Capacity Manual (HCM) methods to a variety of planning applications. PURPOSE The goal of this Guide is to improve planning practice by identifying appropriate methods and applications for employing the HCM in planning and preliminary engineering analyses, illustrating them with case studies. The Guide covers: A. The appropriate use of HCM for a broad spectrum of planning and preliminary engineering applications (including different stages, different scales, and system performance monitoring); B. The appropriate uses for different parts of the HCM (e.g., appropriate use of default values); C. The use of the HCM in scenario planning; D. The coordinated use of HCM with simulation models, travel demand forecasting models, mobile source emissions models, multimodal transportation analysis tools, and other tools; and E. The use of the HCM in evaluating oversaturated conditions in a planning context. The Guide is intended to be used by planning, preliminary engineering, and traffic practitioners at various stages of the system management, operation, planning, and project development process. TARGET AUDIENCE The range of potential users for the Guide includes every technical professional involved in estimating the need for and benefits of highway capacity, monitoring, management and operations investments. This includes all current HCM users, plus planners and travel demand modelers that may not consider themselves HCM users but have used pieces of the HCM in the past. University students in the areas of transportation planning and transportation engineering are also a part of the target audience. HOW TO USE THE GUIDE The Guide is intended to support statewide and local use of HCM methods in the evaluation of current and future traffic operations, and multimodal level of service. The Guide is not intended to replace the Highway Capacity Manual or to specify what constitutes good planning and preliminary engineering analysis. In many cases current practices may be and are superior to the guidance included in the Guide because local practices have been validated for local conditions (all of which cannot be reasonably anticipated in any single national guide). 13

14 ORGANIZATION Part I provides the gateway to the Guide. The chapters in this Part describe typical planning and preliminary engineering analysis needs, identify points where a Highway Capacity Manual (HCM) analysis can provide useful inputs to the analysis, and points the reader to the appropriate part of the Guide where guidance is given on how to apply and adapt as necessary the HCM procedures for use in planning and preliminary engineering analyses. Part I also provides information on working with traffic demand forecasts and predicting future intersection control types. The Part II chapters present guidance on how to apply and adapt the HCM for mid-level planning analyses, those planning analyses that focus on a single facility and its component interchanges, intersections, and segments. Part II also describes how to use default values to reduce the data required to perform HCM analyses. The Part III chapters present guidance on how to extend the HCM for high-level planning analyses involving systems and areawide analyses. Part III also covers the use of service volume tables and volume/capacity ratios to quickly identify the needed geographic scope of an analysis. Part IV presents case studies illustrating the application of the HCM to planning and preliminary engineering analyses that were described in the previous chapters. SCOPE The Guide is intended to support statewide and local use of HCM methods in the planning and preliminary engineering evaluation of current and future traffic operations as well as multimodal level of service. The Guide focuses on the analyses appropriate for each stage of the project life cycle, including: pre-project planning, project needs, project initiation, and environmental clearance (see Exhibit 1). It also introduces procedures for monitoring system performance. The Guide covers: - Long range and short range areawide and corridor planning studies, - Facility specific project and environmental clearance studies, and - Highway performance monitoring. Like the Highway Capacity Manual, the Guide covers the estimation of a variety multimodal transportation performance measures including traffic speed, travel time, delay, density, and queues, as well as auto, truck, bus, bicycle, and pedestrian level of service (LOS). The Guide provides procedures for estimating these performance measures but does not go into how those performance measures are used in planning, programming, and project development. 14

15 Exhibit 1: Scope of the Planning and Preliminary Engineering Applications Guide LEVELS OF ANALYSIS Planning and preliminary engineering covers a wide spectrum of possible levels of analysis. At the highest level (visualize a plane flying at high altitude), the area covered by the analysis is large but the degree of detail (precision) for any particular segment of road is low. This is a typical characteristic of regional areawide studies and sketch planning and screening studies. Highway Capacity Manual analyses using a mix of default and measured inputs are typical mid or medium level analyses. The area covered is significantly reduced, to that of a single facility, or segment/intersection, but the degree of precision in the estimated performance is much improved. Even so, the performance estimates are still at a macroscopic level. A microsimulation analysis provides an extremely low level (highly focused but highly detailed) performance analysis. The Guide focuses on the high and medium level applications of the Highway Capacity Manual to planning and preliminary engineering. 15

16 THE HIERARCHY OF ANALYSIS METHODS The Guide provides in some cases several alternative methods in addition to the standard HCM method to estimating the same performance measure. These alternative methods are designed to better balance the required analysis resources against the accuracy requirements of different levels of planning analysis. For example at a very high sketch planning level or for regional demand modeling purposes, it may be satisfactory to estimate free-flow speed for all facilities using the posted speed limits. For environmental clearance analyses of specific improvements to specific facilities (an example of a preliminary engineering analysis) it may be more appropriate to use the HCM methods for estimating the free-flow speeds. Thus the Guide may provide several methods for estimating performance measures, and will provide advice on what level of planning or preliminary engineering analysis each method may be most suitable for the particular analysis objectives. Generally, when one can measure a performance measure directly in the field, it is usually (but not always) better than estimating that measure indirectly using the HCM or the methods in this Guide. When conditions make it difficult to accurately measure the performance measure in the field, then the Guide takes the perspective that an HCM analysis using field measured inputs is most accurate, followed by an HCM analysis using a mix of default values and field measured inputs, followed by the alternative analysis methods described in the Guide. The general hierarchy of methods (see Exhibit 2) is as follows: Exhibit 2: Relative Effort and Precision of Traffic Performance Estimation Methods 16

17 - Field Measurement is most reliable if it can be done cost-effectively and accurately. Note that the resources required to directly measure performance measures in the field can vary widely, depending on the performance measure and the geographic and temporal scope of the measurement. - Microsimulation modeling of performance is next most accurate if adequate resources are invested in calibrating and validating the model. - HCM estimates of performance using field measured inputs are generally next most accurate. - HCM estimates of performance using a mix of defaults and field measured inputs are usually next most accurate. - Alternative planning methods described in the Guide for estimating performance will usually be the least accurate, but will be among the most cost-effective methods for obtaining estimates of existing and future performance. 17

18 CHAPTER 2 MID-LEVEL (FACILITY SPECIFIC) ANALYSES This chapter describes planning and preliminary engineering analyses that are performed at the medium level of analysis. This level of analyses typically focuses on a specific facility or specific segments, interchanges, and intersections on that facility. Examples of these types of studies include preliminary or conceptual design studies to determine the number of required lanes and traffic/transit/environmental impact studies required to obtain project approval and environmental clearance. While the data requirements of this level of analysis can be fairly extensive, the Highway Capacity Manual, the Guide, and other publications like the Transit Capacity and Quality of Service Manual provide default values for some of the required input to assist in a planning or preliminary engineering analysis. 1. PROJECT TRAFFIC AND ENVIRONMENTAL IMPACT STUDIES A project traffic and environmental impact study focuses on predicting the impacts of one or more specific transportation improvement or land development projects. (For typical analysis guidelines for these types of studies, see these references: [1] [2] [3]) Typical Project Impact and Alternatives Analysis Process Typical project traffic and environmental impact analyses employ manual analysis techniques to add the project generated traffic onto existing or forecasted future traffic and evaluates the impacts on highway facility performance. The impact analysis may extend to other travel modes, such as trucks, buses, bicycles, and pedestrians, and may extend to include vehicle emissions analysis for air quality analyses and a noise analysis. The objective of these impact studies is to identify the project s performance impacts by travel mode, determine if those impacts are significant, generate mitigation measures for those impacts, and assess whether those mitigations can reduce the project impacts to a less - than - significant level. Typical Tools Used In Project Impact and Alternatives Analysis Traffic, transit, and environmental impact analyses typically employ relatively simple manual traffic forecasting techniques and then invest most of their effort in employing HCM type analysis tools for predicting the resulting highway performance for each travel mode (auto, truck, bus, bicycle, and pedestrian). Microsimulation modeling may be employed for the operations analysis of more complex projects where the interactions between queuing and operation performance are expected to be significant. 18

19 If a regional demand model is used to assist in the demand forecasting then some of the methods described in a later section high level methods may be useful for improving the demand model forecasts used in the project impact analysis. Air quality and noise analysis models may be applied to the forecasted traffic to estimate the project s air and noise impacts. Basic Data Needs for Project Impact & Alternatives Analysis The basic data needs for impact analysis include: - Project description - Expected influence area for project impacts - Existing and forecasted demands at key intersections, freeway mainline sections, and ramps - Highway network data o Segments (length, facility type, lanes, geometric cross section) o Intersections (turn lanes, geometric cross-section, signal control settings) - Transit data o Routes, frequencies, bus stop characteristics - Bicycle and pedestrian data o Street and intersection cross-sections, bicycle and pedestrian facility characteristics How the HCM Can Support Project Impact and Alternatives Analyses The HCM can be used to support the project impact analysis tasks shown in Exhibit 3. This exhibit lists the sections of Part II of the Guide where the specific methods are described. The exhibit then lists the example problems in the Part IV case studies where the applications of the methods to typical planning analyses are illustrated. 2. USING DEFAULTS TO REDUCE DATA NEEDS Defaults can be used for many of the traffic characteristics parameters (e.g. percent heavy vehicles, peak hour factor, etc.) required in a typical HCM analysis. Other defaults may be used to characterize the geometric design of the facility (e.g. lane widths, lateral clearance, etc.) when the analyst is confident that the facility generally meets agency standards. Default values for less critical inputs to HCM analyses are provided in each procedural chapter of the 2010 HCM. Additional values are provided in NCHRP Report 599 [1] along with sensitivity analyses of the effects of different values on the results. The Guide provides guidance on the selection and use of default values in Chapter 6 Default Values to Reduce data Needs. 19

20 Exhibit 3: Project Impact Analysis Task Cross Reference Table Project Impact & Alternatives Analysis Task Parts II & III Reference Part IV Case Studies Input to Travel Demand Models (if used) - Estimate highway capacities, and free-flow speeds Chapter 18 Case III Traffic Assignment Module within Travel Demand Model (if used) - Volume-delay functions for estimating congested speeds Chapter 18 Case III Input to Microsimulation Model (if used) - Estimate free-flow speeds Chapters Microsimulation Model Validation and Error Checking (if used) - Estimate capacity for error checking simulated bottlenecks Chapters Project Impact and Alternatives Analyses - Estimate segment speeds for air quality and noise analyses Chapters 8-14 Cases I, II - Estimate auto utilization (v/c) Chapters 8-14 Cases I, II - Estimate of delay Chapters 8-14 Cases I, II - Estimate of queuing Chapters 8-14 Cases I, II - Interpret results Chapters 8-14 Cases I, II - Analyze travel time reliability Chapters 8, 11 Cases I, II - Estimate multimodal quality of service for autos, trucks, transit, bicycles, and pedestrians Chapters 15, 16 Case II Corridor Analyses Chapter REFERENCES 1. Zegeer, John D.; M. Vandehey, M. Blogg, K. Nguyen, M. Ereti, Default Values for Highway Capacity and Level of Service Analysis, Transportation Research Board, Washington, DC,

21 CHAPTER 3 HIGH LEVEL ANALYSES This chapter describes planning and preliminary engineering analyses that are performed at a high level of analysis. These analyses typically cover large areas and systems of facilities. These high level analyses may also be performed as a screening analysis, when one is attempting to determine what the geographic and temporal limits should be for a more detailed level of analysis. Examples of these types of studies include long and short range regional transportation plan analyses, and transportation system performance monitoring studies. These types of studies cover a high number of miles of roadway for a given investment in data collection and analysis resources. 1. SCREENING AND SCOPING STUDIES Scoping studies seek to quickly determine the geographic and temporal limits required for more detailed analyses. Alternative screening studies seek to quickly identify which improvement alternatives may be worthy of further consideration and analysis. Role of the HCM in Screening and Scoping The service volume tables in the Highway Capacity Manual (HCM) can be used to spot facilities, segments and intersections not meeting (or likely to meet) the agency s level of service standards for autos, trucks, bus transit, bicyclists, and pedestrians. Tables of capacities by facility type can be constructed for local facility conditions using local defaults and the HCM procedures. These tables then can be used to quickly identify volume/capacity problems for individual facilities, segments, and intersections, as well as to evaluate the reserve capacity available in a corridor. Improvement alternatives can be quickly compared based on their effect on facility or corridor volume/capacity ratios to identify those alternatives delivering a target v/c ratio. Exhibit 4 lists the specific tasks that can be supported by the HCM. How to Use the Guide for Screening and Scoping Exhibit 4 lists the sections of Part III where the specific methods are described. This table then lists the example problems in the Part IV Case Studies where the applications of the methods to typical planning analyses are illustrated. 21

22 Exhibit 4: Screening and Scoping Task Cross Reference Table Screening and Scoping Task Parts II & III References Part IV Case Studies Identify Potential Level of Service Hot Spots - Screen for Auto LOS Problems Chapters 8-11 Cases I & II - Screen for Truck LOS Problems Chapter 16 Cases I & II - Screen for Transit, Bike, Ped LOS Problems Chapter 15 Case II Identify Potential Capacity Problems - Auto Chapters 8-11 Cases I & II Preliminary Evaluation of Improvement Alternatives - Auto Improvements Chapters 8-11 Cases I & II - Truck Improvements Chapters 8-11 Cases I & II - Transit, Bike, Ped Improvements Chapters 8-11 Cases I & II 2. LONG AND SHORT RANGE AREA-WIDE TRANSPORTATION PLANNING Long range area-wide transportation planning, specifically the production of state and regional long range transportation plans (LRTPs) defines the 20+-year vision for the region s or state s transportation systems and services. Short range areawide planning focuses on just as large an area but on a shorter time frame. In metropolitan areas, the LRTP is the official multimodal transportation plan addressing no less than a 20-year planning horizon that is developed, adopted, and updated by the metropolitan planning organization (MPO) through the metropolitan transportation planning process (MTPP). [4] Typical Areawide Planning Analysis Process In the long range transportation planning process, planners assess future investments based on the performance of the freeways and streets that make up a regional transportation system. The performance of the system and its components are often estimated through a travel demand and analysis forecasting process. This process requires a variety of inputs and analytical methodologies, which the HCM can provide. Typical Tools Used in the Areawide Planning Analysis A combination of specialized travel demand models, geographic information systems (GIS), and spreadsheets are typically used when conducting analyses for long-range transportation plans. The region to be modeled is divided into zones and a highway and a transit network are coded. The GIS, in combination with a land use model, is used to develop forecasts of socio-economic activity (population, employment, etc.) for the region. Basic Data Needs for Areawide Planning Analysis Data needs are kept relatively simple (in terms of different types of data), but end up being massive in size because of the large areas often covered in regional transportation plans. The basic data needs for LRTP s include: - Socio economic data by traffic analysis zone (e.g., population, employment, etc.) - Highway network data 22

23 o Segments (e.g., length, facility type, lanes, capacity, free-flow speed) o Connectivity - Transit network data o Segments, routes, frequencies, transfer points How the HCM Can Support Areawide Planning Analyses The HCM can be used to support the LRTP planning analysis tasks shown in Exhibit 5. This exhibit lists the sections of Part III of the Guide where the specific methods are described. This exhibit then lists the example problems in the Part IV case studies where the applications of the methods to typical planning analyses are illustrated. Exhibit 5: Areawide Planning Analysis Task Cross Reference Table Areawide Planning Analysis Task Part III Reference Case Studies Input to Travel Demand Models - Estimate highway segment capacities, and free-flow speeds Chapter 18 Case III Traffic Assignment Module within the Travel Demand Model - Provide volume-delay functions to estimate congested speeds Chapter 18 Case III Post-processing Travel Demand Model Outputs - Obtain more accurate speed estimates for air quality analyses Chapter 18 Case III - Spot auto v/c and LOS hot spots (quick screening) Chapter 18 Case III - Estimate delay based on agency policy Chapter 18 Case III - Estimate queuing Chapter 18 Case III - Interpret results Chapter 18 Case III - Analyze travel time reliability Chapter 18 Case III - Estimate multimodal quality of service for autos, trucks, transit, bicycles, and pedestrians Chapters 15, 16 Case III Corridor Analyses Chapter SYSTEM PERFORMANCE MONITORING Highway system performance monitoring is the measurement of highway use and operating characteristics under existing conditions. [5] Performance Monitoring Context The Moving Ahead for Progress in the 21 st Century Act (MAP-21) established a performance and outcome based program for states to invest resources in projects that collectively will make progress toward the achievement of national goals. [6] MAP-21 requires FHWA to work with stakeholders to identify performance measures tied to seven goal areas for the federal air highway program: - Safety - Infrastructure Maintenance 23

24 - Congestion Reduction - System Reliability Improvement - Freight Movement and Economic Vitality - Environmental Sustainability - Reduced Project Delivery Delays Of these seven goal areas, the HCM can assist agencies in monitoring highway performance relevant to the two goal areas of Congestion Reduction and System Reliability Improvement Role of the HCM in Performance Monitoring The HCM can be used to compute the performance measures not directly monitored at a monitoring site. It can be used to spot data errors and inconsistencies. It can be used to impute missing performance data. Exhibit 6 lists the specific performance monitoring tasks that can be supported by the HCM. How to Use the Guide for Performance Monitoring Exhibit 6 lists the sections of Part III where the specific methods are described. This table then lists the example problems in the Part IV case studies where the applications of the methods to typical planning analyses are illustrated. Exhibit 6: Performance Monitoring Task Cross Reference Table Performance Monitoring Task Part III Reference Part IV Case Studies Estimate monitoring site capacities, and free-flow speeds For Volume Only Monitoring Sites - Estimate speeds Chapter 18 Case IV For Travel Time Only Monitoring Segments - Estimate volumes - Case IV Performance Analyses - Quality Assurance/Quality Control - Case IV - Auto and truck vehicle miles traveled (VMT) Chapter 18 Case IV - Auto and truck VMT by LOS Chapter 18 Case IV - Estimate delay Chapter 18 Case IV - Estimate queuing Chapter 18 Case IV - Analyze travel time reliability Estimate multimodal LOS for trucks, transit, bicycles, and pedestrians Chapter 18 Case IV 24

25 4. REFERENCES 1. CH2MHill, Best Practices for Traffic Impact Studies, Oregon Department of Transportation, Salem, OR, June Development Review Guidelines, Oregon Department of Transportation, Salem, OR, California Environmental Quality Act, 2014 CEQA Statute and Guidelines, Association of Environmental Professionals, Palm Desert, CA, January The Transportation Planning Process Key Issues, A Briefing Book for Transportation Decision makers, Officials, and Staff. FHWA-HEP , Federal Highway Administration, Washington DC, Accessed September 2, Accessed September 2,

26 CHAPTER 4 WORKING WITH TRAFFIC DEMAND DATA 1. OVERVIEW The traffic demand data available for a planning or preliminary engineering analysis may require adjusting before it can be used with an HCM planning method. For example, average annual daily traffic (AADT) volumes may need to be converted to hourly volumes representative of the conditions of interest to the analysis (e.g., peak-hour, peak-season volumes). This section provides guidance on these types of demand volume adjustments. The analyst should be aware that state and local traffic forecasting and analysis guidelines and policies often specify the methods that should be used to adjust demand volumes, as well as the analysis hour(s) that should be analyzed. It is important for planning and preliminary engineering analyses to follow these local guidelines, in part because any subsequent operational analyses will apply the same guidance. The goal is for the more-detailed study to focus on the specific issues identified by the earlier, more-general study, and not to have to redo prior work because the wrong procedures were used. Therefore, it is recommended that the analyst check whether state and local guidelines already exist prior to applying the guidance found in this section. NCHRP Report 255 [8] and NCHRP 765 [11] are good references on how to process demand model forecasts for use in traffic analyses. 2. SELECTION OF AN ANALYSIS HOUR One important decision when performing a traffic analysis is the selection of an analysis hour. This choice balances a transportation agency s desire to provide adequate operations during the large majority of hours of the year and its need to use its limited resources as efficiently as possible. AASHTO (2011) recommends the use of the 30th-highest hour of the year as a design hour, resulting in a few hours per year with (sometimes substantially) higher volumes and many hours per year with lower volumes. Some agencies choose other analysis hours for cost-efficiency reasons; for example, Florida uses a combination of the 100th-highest hour (for areas under 50,000 population) and a typical weekday peak hour (for larger areas) (Florida DOT 2014). In some cases, the needs of the analysis may require using a non-weekday peak hour (e.g., special event planning, transportation planning for recreation areas). The choice of an analysis hour will affect the way traffic volumes may need to be adjusted for use with HCM methods. 26

27 3. CONVERTING DAILY VOLUMES TO SHORTER TIMEFRAMES HCM methods work with hourly directional demand volumes as a starting point and typically analyze traffic flows during the peak 15 minutes of an analysis hour. Sometimes, however, the traffic demand volumes available for a planning analysis consist of AADTs. These must be converted into peak directional volumes. Three factors are used in this process: the K-factor (the proportion of AADT occurring during the analysis hour), the D-factor (the proportion of traffic in the peak direction during the analysis hour, and the peak hour factor (PHF, converting design-hour volumes to the equivalent hourly flow that occurs during the peak 15 minutes). K-Factor The K-factor converts AADT to analysis hour volumes. It is the percentage of AADT occurring during the analysis hour. The selection of an appropriate K-factor is very important, as selecting a value that is too high can result in too many locations being identified as having not meeting roadway operations standards (as the resulting estimated hourly volumes are too high), while selecting a value that is too low can result in some problem locations not being identified (because the estimated hourly volumes are too low). The former may result in unnecessary follow-up work and potentially too bleak a picture of future conditions, while the latter may result in potentially important problems going undetected. For many rural and urban highways, the K-factor falls between 0.09 and For highways with strongly peaked demand, the K-factor may exceed Conversely, for highways with consistent and heavy flows for many hours of the day, the K-factor is likely to be lower than In general, The K-factor decreases as the AADT on a highway increases; The K-factor decreases as development density along a highway increases; and The highest K-factors occur on recreational facilities, followed by rural, suburban, and urban facilities, in descending order (HCM 2010). In addition, the K-factor will be higher when a 30th-highest hour is chosen as the analysis hour (K 30 ) than when the 50th- (K 50 ) or 100th-highest hour (K 100 ) is used. The K-factor should be determined, if possible, from local data for similar types of facilities with similar demand characteristics. Data from the automatic traffic recorders maintained by state DOTs and other transportation agencies are a good source for these data. Exhibit 7 presents illustrative K 30 values, on the basis of average data from Washington State that demonstrate how K-factors decrease as AADT increases (HCM 2010). 27

28 Exhibit 7: Illustrative K 30 Values. AADT Average K , ,500 5, ,000 10, ,000 20, ,000 50, , , , , >200, Sources: HCM 2010 Exhibit 3-10, Washington State DOT (2008). D-Factor The D-factor represents the proportion of traffic in the peak direction on a roadway during the peak hour. Radial roadways into a city center and recreational and rural routes are often subject to strong directional imbalances during peak hours. In contrast, circumferential roadways and routes connecting major cities within a metropolitan area may have very balanced flows during peak periods. Exhibit 8 presents illustrative directional distributions derived from selected California freeways (HCM 2010). Exhibit 8: Illustrative D-Factor Values. Freeway Type D-Factor Rural intercity 0.59 Rural recreational and intercity 0.64 Suburban circumferential 0.52 Suburban radial 0.60 Urban radial 0.70 Intra-urban 0.51 Sources: HCM 2010 Exhibit 3-11, 2007 Caltrans data. Directional Design-Hour Volume The directional design-hour volume (DDHV) is the starting point for many HCM-based analyses. It can be calculated by multiplying the AADT by the K- and D-factors, as shown in Equation C-1 (HCM 2010). Where DDHV = AADT K D Equation C-1 DDHV = directional design-hour volume (veh/h), AADT = annual average daily traffic (veh/day), 28

29 K = proportion of AADT occurring in the peak hour (decimal), and D = proportion of peak-hour traffic in the peak direction (decimal). Note that a toll facility may have different peaking (K-factors) than similar untolled facilities. Peak Hour Factor Most HCM methods analyze conditions during the peak 15 minutes of the peak hour. Although this may seem to be a fairly short timeframe on which to base roadway design and control decisions, it should be kept in mind that the effects of roadway operations breaking down at a single location can last for much longer periods of time (potentially hours in larger metropolitan areas) and that the ripple effects of a breakdown can extend to other roadway segments and intersections. Therefore, the HCM analyzes the peak 15 minutes, to evaluate the worst-case situation that can lead to facility breakdowns. In the absence of direct measurements of peak-15-minute volumes (a common situation for planning analyses), a peak hour factor (PHF) is used to convert hourly demand volumes into the equivalent hourly flow rate if the peak-15-minute volume were sustained over an entire hour. The PHF is calculated as shown in Equation C-2, with the peak-15-minute flow rate calculated as shown in Equation C-3 (HCM 2010). Where PHF = v = V 4 V 15 Equation C-2 V PHF PHF = peak hour factor (decimal), V = hourly volume (veh/h), V 15 = volume during the peak 15 min of the analysis hour (veh/15 min), and v = flow rate for a peak 15-min period (veh/h). Equation C-3 As with the K-factor, the selection of an appropriate PHF strongly influences the accuracy of the analysis results. For high level planning analyses it is often appropriate (given the amount of uncertainty in some of the inputs, like demand) to evaluate average hourly conditions, in which case the PHF is set to For medium level preliminary engineering studies it may be more appropriate to use field measured PHF s or the default PHF s suggested in the HCM or NCHRP Report 599 [13]. 4. SEASONAL ADJUSTMENTS TO TRAFFIC VOLUMES Sometimes when peak-hour or peak-15-minute traffic counts are available for a planning or preliminary engineering analysis, the time of year when the counts were made may not correspond to the desired analysis hour. In these cases, the counts need to be adjusted to represent analysis hour volumes. The basic adjustment process is to factor the counts by the ratio of the average monthly volume for a month reflective of the analysis hour to the average monthly volume during the month when the counts 29

30 were made. Data from the automatic traffic recorders maintained by state DOTs and other transportation agencies are a good source for average monthly traffic volumes. Alternatively, tables of monthly factors (the ratio of monthly average volume to AADT) for each month of the year for specific count stations or for particular types of facilities may be available from transportation agencies (again, based on automatic traffic recorder data). In these cases, the counts can be factored by the ratio of the monthly factor for a month reflective of the analysis hour and the monthly factor for the month when the counts were made. 5. ROUNDING TRAFFIC VOLUMES The traffic volumes used for planning and preliminary analyses are often estimates. Therefore, to avoid giving the impression of a greater degree of accuracy than is warranted, AASHTO recommends rounding traffic volumes as follows (AASHTO 2011): Volumes under 1,000 should be rounded to the nearest 10. Volumes between 1,000 and 9,999 should be rounded to the nearest 100. Volumes of 10,000 or more should be rounded to the nearest 1, DIFFERENCES BETWEEN OBSERVED VOLUMES AND ACTUAL DEMAND HCM methods typically require demand volumes, the traffic volume that would use a roadway during an analysis hour in the absence of any capacity constraints (i.e., bottlenecks). Field measurements of traffic volumes produce observed volumes, the traffic volume that is capable of using a roadway during an analysis hour. When demand is less than capacity (under saturated flow) and no bottlenecks exist upstream, then the demand volume can be assumed to be equal to the observed volume. When demand exceeds capacity (oversaturated flow), then determining demand requires a count of the traffic joining the queue upstream of the bottleneck, as opposed to a count of traffic departing the bottleneck (Robertson and Hummer 2000). However, it may not be easy to determine how much of the traffic joining the queue is bound for the bottleneck location once the queue extends past the previous intersection or interchange (as some traffic may intend to exit the roadway at that point) (HCM 2010). 7. CONSTRAINING DEMAND FOR UPSTREAM BOTTLENECK METERING Transportation planning models produce demand volume estimates. However, when a model does not account for the metering effect of bottlenecks (i.e., is not capacity-constrained), it will produce estimates of demand downstream of a bottleneck that are higher than would actually be observed. This can result in HCM based methods predicting level of service F for situations where the traffic physically cannot arrive at the study area. The following procedure, adapted from Appendix F of the FHWA Guidelines for Applying Traffic Microsimulation Modeling Software [3] can be used in a post-processing analysis of demand model outputs to constrain demand forecasts for segments downstream of a bottleneck. Step 1: Identify Gateway Capacities The analyst should first identify the capacities of the facility or facilities at the gateways delivering traffic to the proposed HCM study facility, segment, intersection, or area (see Exhibit 9). These gateways 30

31 cannot physically feed traffic to the HCM facility at a higher rate than their capacity. Any forecasted demands greater than the inbound capacity of a gateway should be reduced to the inbound capacity of the gateway. Step 2: Estimate Excess Demand at Inbound Bottlenecks If the forecasted hourly demand in the inbound direction at a gateway exceeds its capacity, the proportion of the demand that is in excess of the available hourly capacity should be computed: Where: P = proportion of excess demand D = forecasted demand (veh/h) C = estimated capacity (veh/h) P = D C C Equation 1: Proportion of Excess Demand Step 3: Reduce Forecasted Demand within HCM Study Area The forecasted hourly demands for the facilities and segments within the HCM study area that are downstream from the bottleneck should also be reduced. The reduction however must take into account the traffic entering and exiting the facility within the study area. It is suggested that the forecasted downstream demands be reduced in proportion to the reduction in demand that can get through the gateway, assuming that the amount of reduction in the downstream flows is proportional to the reduction in demand at the bottleneck. If the analyst has superior information (such as an O-D table), then the assumption of proportionality should be overridden by the superior information. The gateway constrained downstream demands are then obtained by summing the constrained gateway, off-ramp, and on-ramp volumes between the gateway and the downstream segment. Where: D c = D u (1 P) Dc = constrained demand (veh/h) for a downstream off-ramp or exit point Du = unconstrained demand forecast (veh/h) P = proportion of excess demand Equation 2 31

32 Exhibit 9 illustrates how the proportional reduction procedure would be applied for a single inbound gateway constraint that reduces the peak-hour demand that can get through from 5000 veh/h to 4000 veh/h. Exhibit 9: Capacity Constraining Demands Entering and Within HCM Study Facility Du = unconstrained demand Dc = constrained demand Starting upstream of the gateway, there is an unconstrained demand for 5000 veh/h. Since the gateway has a capacity of 4000 veh/h, the downstream capacity constrained demand is reduced from the unconstrained level of 5000 veh/h to 4000 veh/h. Thus, 1000 vehicles are stored at the gateway during the peak hour. Since it is assumed that the stored vehicles are intended for downstream destinations in proportion to the exiting volumes at each off-ramp and freeway mainline, the downstream volumes are reduced the same percentage as the percentage reduction at the bottleneck (20 percent). A 20-percent reduction of the off-ramp volume results in a constrained demand of 800 veh/h. The on-ramp volume is unaffected by the upstream gateway bottleneck, so its unconstrained demand is unchanged at 500 veh/h. The demand that enters the segment downstream of the interchange is equal to the constrained demand of 4000 veh/h leaving the gateway bottleneck, minus the 800 veh/h leaving the freeway on the off-ramp, plus 500 veh/h entering the freeway at the on-ramp, which results in a constrained demand of 3700 veh/h for the downstream segment. 8. GENERATING TURNING MOVEMENT VOLUME ESTIMATES FROM LINK VOLUMES The HCM s intersection analysis methods require turning movement volumes. However, this information may not be available for planning and preliminary engineering analyses (e.g., when only link volume data are available, or when the turning movements produced by a transportation planning model are not considered to be reliable). In these cases, the following methods for estimating turning movements can be applied, based on NCHRP Report 255. The analyst will need to manually check the results of these methods for reasonableness. (The reader may wish to consult NCHRP Report 765, update of this older report [11]). 32

33 NCHRP Report 255 Combined Method The NCHRP Report 255 combined method (Pedersen and Samdahl 1982); based on a procedure developed by the New York State DOT (Pedutó, Cioffi, and Albertin 1977) can be used to refine the turning movement estimates produced by travel demand models 1. For a given intersection, this method requires the model s base-year volume forecast for each intersection movement, the model s futureyear volume forecast for the same movements, and actual turning movement volumes for the base year. First, the ratio of the base-year count to the model s base-year forecast is calculated for a given movement, and the future-year forecast is multiplied by this ratio. For example, if the base-year count is 500 veh/h, the base-year forecast is 400 veh/h, and the future-year forecast is 700 veh/h, the ratio is (500/400), or Multiplying 700 by 1.25 results in a future volume estimate of 875. Second, the difference between the base-year count and the base-year forecast is calculated and added to the future-year forecast. Continuing the example from the above, the difference is ( ), or 100. Adding 100 to 700 results in a future volume estimate of 800. Last, the two turning movement estimates are averaged to produce the final estimate. In this case, the average of 875 and 800 are averaged to obtain 838. Following the rounding guidance provided earlier, this value would then be rounded up to 840. This method can be readily calculated by hand or implemented in a simple spreadsheet. However, it requires base-year turning movement counts, which may not be available, and the resulting turning movement estimates will not match the model s intersection entry and departure link volumes. Consequently, some further manual balancing of volumes between intersections may become necessary. NCHRP Report 255 Iterative Method The NCHRP Report 255 iterative method is useful when preserving link entry and departure volumes is important to the analysis. Although knowing current turning movement percentages is helpful in minimizing the number of iterations required by the method, it is not essential. The method can use link volumes directly, or can estimate them by applying K- and D-factors to AADT or analysis hour volumes. The HCM2000 described the method as follows: Each approach to the intersection is considered an origin. Each departure leg is a destination as shown in Exhibit 10. The problem then becomes one of estimating the origin-destination (O-D) table given the entering and exiting volume on each leg of the intersection. 1 This may be incorrectly cited: this reference actually is Highway Traffic Data for Urbanized Area Project Planning and Design, Issue 255 and not NCHRP 255. I re-wrote the turning movements Chapter 8 from NCHRP 255 in NCHRP 765 and did not recall seeing this method there Tom Creasey. 33

34 Exhibit 10: Origin-Destination Labels for Intersection Turning Movements Source: HCM2000, Exhibit The procedure assumes that the number of vehicles going from one leg to another is directly proportional to the total volume entering the one leg and the total volume exiting on the other leg. This assumption may not be valid when other factors or geometric situations are present, such as a nearby freeway on-ramp, which may attract a much higher than normal trip volume. Equation C-4 is used to estimate the turning movement O-D matrix: T ij = T i T j i T ij Equation 3 Where T ij = number of trips going from origin leg i to destination leg j, T i = number of trips originating at origin i, and T j = number of trips leaving at destination j. U-turns (T i = j ) trips are assigned a value of zero unless the analyst is aware of a reason for U-turns to be a significant number. Note that Equation C-4 does not ensure that the final estimates of total trips exiting each leg of the intersection will match the initial value. An iterative procedure can be used to increase or reduce the T ij as necessary to ensure that the sum of the T ij is close to the initial demand estimates for each entering and departing leg of the intersection. This procedure is known as a matrix balancing process (Ortuzar and Willumsen 1994). The steps of the iterative procedure use Equations C-5 through C-8. Step 1. Compute the ratio of desired to actual exiting volume for each departure leg. R j = T j i T ij 34

35 Equation 4 Where R j = ratio of desired to actual exiting volume for exit leg j, T j = desired exiting volume for exit leg j, and T ij = current estimate of volume going from origin i to destination j. Step 2. Multiply all T ij for that exit leg by ratio R j. Repeat for each exit leg. Step 3. Compute ratio of desired to actual entering volumes for each entering leg i. R i = T i j T ij Equation 5 Where R i = ratio of desired to actual entering volume for entry leg i, T i = desired entering volume for entry leg i, and T ij = current estimate of volume going from origin i to destination j. Step 4. Multiply all T ij for that entry leg by ratio R i. Repeat for each entry leg. Step 5. Determine whether the user-specified number of iterations has been exhausted or the userspecified closure criterion is met for all entry (diff i ) and exit (diff j ) legs. diff i = T i T ij for entry legs j diff j = T j T ij for exit legs i Equation 6 Equation 7 Step 6. If any of the computed differences is greater than the closure criterion (a closure criterion of 10 veh/h is suggested) and the iteration limit has not been exceeded, then go back to Step 1. Florida DOT Method FDOT uses a method originally described by Hauer, Pagitsas, and Shin (1981). An initial estimate of the proportion of an approach s traffic turning right, turning left, or continuing straight can be provided by the user (for example, from existing turning movements), or the method can create its own first-guess proportions from the approach volumes. Once the turning proportions have been specified, the method goes through a series of iterations similar to the NCHRP Report 255 Iterative Method to develop the 35

36 turning movement estimates. As with the Iterative Method, the FDOT method is useful when it is desirable to preserve the link entry and exit volumes in the analysis. FDOT has developed the TURNS5 spreadsheet ( to assist analysts with implementing this method (Florida DOT 2014). 9. REFERENCES 1. American Association of State Highway and Transportation Officials. A Policy on Geometric Design of Highways and Streets. Washington, D.C., Florida Department of Transportation. Project Traffic Forecasting Handbook. Tallahassee, Dowling, R.G., A. Skabardonis, V. Alexiadis, Traffic Analysis Toolbox Volume III, Guidelines for Applying Traffic Microsimulation Software, FHWA-HRT , Federal Highway Administration, Washington, DC, June Hauer, E., E. Pagitsas, and B.T. Shin. Estimation of Turning Flows from Automatic Counts. In Transportation Research Record 795, Transportation Research Board, National Research Council, Washington, D.C., Highway Capacity Manual Transportation Research Board, National Research Council, Washington, D.C., Highway Capacity Manual Transportation Research Board of the National Academies, Washington, D.C., Ortuzar, J. D., and L. G. Willumsen. Modeling Transport, 2nd Edition. John Wiley and Sons, New York, Pedersen, N. J., and D. R. Samdahl. NCHRP Report 255: Highway Traffic Data for Urbanized Area Project Planning and Design. Transportation Research Board, National Research Council, Washington, D.C., Dec Pedutó, F., G. Cioffi, G. and R. Albertin, R. Documentation of Selected Programs of the NYSDOT s Simulation System. New York Department of Transportation, Albany, June Robertson, H. D., and J. E. Hummer. Volume Studies. In Manual of Transportation Engineering Studies (H. D. Robertson, J. E. Hummer, and D. C. Nelson, eds.), Institute of Transportation Engineers, Washington, D.C., Smith, CDM, A. Horowitz, T. Creasey, R. Pendyala, Mei Chen; Analytical Travel Forecasting Approaches for Project-Level Planning and Design, NCHRP Report 765, Transportation Research Board, Washington, DC, Washington State Department of Transportation. Peak Hour Report: Year Transportation Data Office, Olympia, Zegeer, John D.; M. Vandehey, M. Blogg, K. Nguyen, M. Ereti, Default Values for Highway Capacity and Level of Service Analysis, Transportation Research Board, Washington, DC,

37 CHAPTER 5 PREDICTING INTERSECTION TRAFFIC CONTROL 1. OVERVIEW Analyzing the operation of an urban street using the HCM requires some knowledge of the type of traffic control used at the intersections along the street. When analyzing future conditions as part of a planning or preliminary engineering analysis, decisions may not have been made about the type of traffic control used at an intersection, or the purpose of the analysis may be to determine the type of traffic control that would likely needed in the future under a particular analysis scenario. This section provides guidance on forecasting what type of traffic control may be needed at an intersection in the future, for use in preparing inputs to an HCM analysis. It also provides guidance on developing traffic signal timing inputs for use in a planning-level signalized intersection analysis using HCM methods. The analyst should be aware that state and local policies may often specify the conditions under which particular types of intersection traffic control should or should not be considered. These policies supersede the guidance presented in this section. 2. MANUAL ON UNIFORM TRAFFIC CONTROL DEVICES FHWA s Manual on Uniform Traffic Control Devices (MUTCD, 2009) provides warrants and criteria to help in determining whether a traffic signal or all-way STOP control may be justified at an intersection. Meeting one or more warrants does not automatically mean a particular type of traffic control is justified, but not meeting the warrants generally means that that type of traffic control would not be justified. State supplements to the MUTCD, or state or local policies, may specify that certain warrants found in the MUTCD should not be used, and planning studies should respect those policies. Determining 8th- and 4th-Highest Hour Volumes The most commonly applied MUTCD warrants require determining the 8th- or 4th-highest hour traffic volumes. The decision to actually install a traffic signal would normally be performed on the basis of actual traffic counts, but when a planning or preliminary engineering analysis is being performed, future volumes are being estimated and typically only in the form of AADTs or peak-hour volumes. Therefore, some other means is required to estimate what the 8th- or 4th-highest volumes would be. Possible methods for doing so include the following, in order of preference: Calculate the ratio of 8th- (or 4th-) highest hour traffic volumes to peak hour traffic volumes using recent traffic counts from the intersection or a similar intersection. 37

38 Calculate the ratio of 8th- (or 4th-) highest hour traffic volumes to peak hour traffic volumes using data from a permanent traffic recorder in the area. Apply a factor to the peak-hour traffic volume. The specific factor will depend on how peaked the peak hour is. For example, when peak-hour traffic represents 7.8% of AADT, the 4th-highest hour volume is approximately 90% of the peak-hour volume, while the 8th-highest hour is approximately 80% of the peak-hour volume (May 1990). On the other hand, when peak-hour traffic represents 10.6% of AADT, the 4th-highest hour volume is approximately 67% of the peak-hour volume, and the 8th-highest hour volume is approximately 55% of the peak-hour volume (ITE 1982). In both cases, the 4th-highest volume represents approximately 70% of AADT, while the 8th-highest volume represents approximately 60% of AADT. Applying MUTCD Warrants The basic information needed to apply the MUTCD warrants is listed in Exhibit 11. Exhibit 11: Required Data for MUTCD Warrant Analysis For For For Input Data (units) Default Value 8HR 4HR AWS 8th-highest vehicular volume by approach 60% of AADT (veh/h) Number of lanes on major street approach Must be provided Number of lanes on minor street approach Must be provided Major street speed (mi/h) Posted speed City population < 10,000 (yes/no) Must be provided 4th-highest vehicular volume by approach 70% of AADT (veh/h) Peak hour minor street delay (s/veh) Must be provided Notes: See MUTCD Section 4C for definitions of the required input data and additional guidance. 8HR = 8-hour signal warrant, 4HR = 4-hour signal warrant, AWS = all-way stop warrant. Once the required data are available, the appropriate sections of the MUTCD are consulted to determine whether the traffic volumes would satisfy one or more warrants, given the other conditions (e.g., number of lanes, major street speed) existing at the intersection. These are: Section 4C.02 for the eight-hour traffic signal warrant, Section 4C.03 for the four-hour traffic signal warrant, and Section 2B.07 for the all-way stop control criteria. 38

39 3. PREDICTING FUTURE INTERSECTION TRAFFIC CONTROL As an alternative to evaluating the MUTCD traffic signal warrants (see Section D2), graphical methods can be used to predict what the future intersection traffic control will be. These methods have the advantage of requiring less data than a signal warrant evaluation does, but have the disadvantage of built-in assumptions that may not be appropriate for a given location. Exhibit 12 can be used to determine the likely future intersection traffic control, using only peak-hour two-directional volumes for the major and minor streets as inputs. Exhibit 12: Intersection Control Type by Peak Hour Volume Source: Adapted from HCM2000 with the addition of roundabout ranges. Single-lane roundabout capacity from Rodegerdts et al. (2010). Notes: AWSC = all-way STOP control, TWSC = two-way STOP control. Uses 8-hour MUTCD traffic signal warrants converted to two-way peak-hour volumes assuming ADT equals twice the 8-hour volume and the peak hour is 10% of the daily volume. Two-way volumes assumed to be 150% of the peak-direction volume. TWSC LOS C/D threshold used for lower limit of single-lane roundabout. 39

40 4 REFERENCES Highway Capacity Manual Transportation Research Board, National Research Council, Washington, D.C., Institute of Transportation Engineers. Traffic and Transportation Engineering Handbook. Washington, D.C., Manual on Uniform Traffic Control Devices. Federal Highway Administration, Washington, D.C., May, A. Traffic Flow Fundamentals. Prentice Hall Publishing, Englewood Cliffs, N.J., Rodegerdts, L., J. Bansen, C. Tiesler, J. Knudsen, E. Myers, M. Johnson, M. Moule, B. Persaud, C. Lyon, S. Hallmark, H. Isenbrands, R. B. Crown, B. Guichet, and A. O Brien. NCHRP Report 672: Roundabouts: An Informational Guide. 2nd Edition. Transportation Research Board of the National Academies, Washington, D.C., Tianxiao, J. and Y. Quan. Control Type Selection at Isolated Intersections Based on Level of Service. Paper Presented at the Transportation Research Board 91st Annual Meeting, Washington, D.C.,

41 CHAPTER 6 DEFAULT VALUES TO REDUCE DATA NEEDS 1. OVERVIEW Many HCM computational methods require a number of input parameters. For a detailed operations analysis, this can be an advantage, as the performance measure output by the method reflects many different factors that can influence the result. For planning and preliminary engineering analyses, however, the number of inputs can pose a challenge, as the desired information may not yet be known, the level of effort required to gather the data may be out of proportion to the aims of the analysis, or some combination of these and other considerations make it difficult to supply a particular input value. One solution to applying HCM methods to planning and preliminary engineering analyses is to substitute default values for those inputs that cannot be measured directly. Using default values instead of fieldmeasured values may introduce some error into the analysis results, but other data used for planning analyses (particularly forecast demand volumes) may have much greater uncertainty associated with their values and, consequently, much greater impact on the results. Furthermore, the goal of these types of analyses is not to make final decisions about roadway design and control elements, but rather to identify potential problems or to screen large numbers of alternatives; in these cases, precise results are neither required nor expected. This section provides guidance on applying default values to HCM methods and on developing local default values to use in place of the HCM s national defaults. 2. WHEN TO CONSIDER DEFAULT VALUES The decision to use a default value in place of a field-measured value should consider a number of factors, including: The intended use of the analysis results. In general, the less precisely that analysis results will be presented (e.g., under/near/over capacity vs. a particular level of service vs. a specific travel speed estimate), the more amenable the analysis is to using default values. Similarly, the farther away a final decision will be (e.g., identifying potential problem areas for further analysis vs. evaluating a set of alternatives vs. making specific design decisions), the less potential for incorrect decisions to be drawn from the analysis results due to the use of a default value. The scale of the analysis. The larger the geographic scale of the analysis (i.e., the greater the number of locations that need to be analyzed), the greater the need to use default values due to the impracticality of collecting detailed data for so many locations. 41

42 The analysis year. The farther out into the future that conditions are being forecast, the more likely that information will not be known with certainty (or at all), and the greater the need to apply default values. The sensitivity of the analysis results to a particular input value. Sections E through M of this guidebook provide information about the sensitivity of analysis results to the inputs used by a given HCM operations method. Input parameters are characterized as having a low, moderate, or high degree of sensitivity, depending on whether a method s output changes by less than 10%, 10% to 20%, or more than 20%, respectively, when an input is varied over its reasonable range. The lower the result s sensitivity to a particular input, the more amenable that input is to being defaulted. Ease of obtaining field or design data. According to the HCM 2010, input parameters that are readily available to the analyst (e.g., facility type, area type, terrain type, facility length) should use actual values and not be defaulted. Inputs essential to an analysis. A few inputs to HCM methods, such as demand volumes and number of lanes, are characterized as required inputs and should not be defaulted. When the purpose of the analysis is to determine a specific value for a required input (e.g., the maximum volume for a given level of service), the HCM method is run iteratively, testing different values of the input until the desired condition is met. Local policy. State and local transportation agencies traffic analysis guidelines may specify that particular inputs to HCM methods can be or should not be defaulted. 3. SOURCES OF DEFAULT VALUES Once a decision has been made to use a default value for a particular methodological input, there are several potential sources for obtaining a default value. These are, in descending order of desirability according to the HCM2010: Measure a similar facility in the area. This option is most applicable when facilities that have not yet been built are being analyzed and the scope of the analysis does not require measuring a large number of facilities. Local policies and standards. State and local transportation agencies traffic forecasting guidelines may specify, or set limits on, default values to assume. Similarly, these agencies roadway design standards will specify design values (e.g., lane widths) for new or upgraded roadways. Local default values. When available, local default values will tend to be closer to actual values than the HCM s national defaults will be. Heavy-vehicle percentage, for example, has been shown to vary widely by state and facility type (Zegeer et al. 2008). Section 4 provides guidance on developing local default values. HCM default values. If none of the above options are feasible, then the HCM s national default values can be applied. 42

43 4. DEVELOPING LOCAL DEFAULT VALUES This section is adapted from HCM 2010 Chapter 6, Appendix A. Local defaults provide input values for HCM methods that are typical of local conditions. They are developed by conducting field measurements in the geographic area where the values will be applied, during the same time periods that will be used for analysis, typically weekday peak periods. For inputs related to traffic flow and demand, the peak 15-minute period is recommended as the basis for computing default values because this time period is most commonly used by the HCM s methodologies (HCM 2010). When an input parameter can significantly influence the analysis results, it is recommended that multiple default values be developed for different facility types, area types, or other factors as appropriate, as doing so can help reduce the range of observed values associated with a given default and thus the error inherent in applying the default. The K- and D-factors used to convert average annual daily traffic (AADT) volumes to directional analysis hour volumes are two such parameters. For urban streets, other sensitive parameters include peak hour factor, traffic signal density, and percent heavy vehicles. For freeways and highways, sensitive parameters include free-flow speed and peak hour factor. 5. REFERENCES Zegeer, J. D., M. A. Vandehey, M. Blogg, K. Nguyen, and M. Ereti. NCHRP Report 599: Default Values for Highway Capacity and Level of Service Analyses. Transportation Research Board of the National Academies, Washington, D.C., Highway Capacity Manual Transportation Research Board, National Research Council, Washington, D.C., Highway Capacity Manual Transportation Research Board of the National Academies, Washington, D.C.,

44 CHAPTER 7 SERVICE VOLUME TABLES TO REDUCE ANALYSIS EFFORT Overview One typical planning application of the HCM is to estimate the existing or future level of service (LOS) of a large number of roadway links. For example, this might be performed as part of a screening evaluation (to identify links requiring more detailed analysis) or as part of an agency s roadway system monitoring program. Generalized service volume tables, which estimate the maximum daily or hourly volume that a roadway can serve under an assumed set of conditions, can be a useful tool for performing these types of evaluations. K- D- Four-Lane Freeways Six-Lane Freeways Eight Factor Factor LOS B LOS C LOS D LOS E LOS B LOS C LOS D LOS E LOS B L Level Terrain For ease of use, generalized service volume tables require a minimum of user inputs typically, key design parameters that have the greatest influence on a facility s capacity and LOS, such as Rolling the number Terrain of lanes. Given these inputs, a user can then read the maximum volume (service volume) for a given LOS 0.08 directly from the table and compare it with the actual or forecast volume for a system element. A volume greater than the service volume for the desired LOS indicates the need for further analysis (HCM 2010). The area type (e.g. urban, rural, etc.) often serves as a proxy for many default values (for example, driver population, percent heavy vehicles, peak hour factor). As such, the area type often has a significant 0.10 effect on the service volumes. It is unlikely that any given roadway s characteristics will exactly match the default values used in 0.11 creating the table. Therefore, conclusions drawn from the use of service volume tables should be considered to be, and presented as, rough approximations. In particular, generalized service volume tables should not be used to make final decisions about important roadway design features this requires a full operational analysis. However, as long as the analyst recognizes and respects the limitations of this tool, generalized service volume tables can be a useful sketch-planning tool for developing quick estimates of LOS and capacity, especially for large numbers of facilities (HCM 2010). When to Consider Service Volume Tables The decision to use a service volume table should consider a number of factors, including: The scale of the analysis. The larger the geographic scale of the analysis (i.e., the greater the number of locations that need to be analyzed), the more applicable service volume tables become due to the impracticality of collecting detailed data for so many locations. When a small 44

45 number of locations are being analyzed, other analysis tools will likely provide a more accurate result, as it becomes more feasible to collect data, apply less-generalized default values, or both. Nevertheless, service volume tables can be applied to smaller sets of locations when the outcome of the analysis does not require a higher level of accuracy. The intended use of the analysis results. Service volume tables are well-suited to analyses where the identification of a potential operational problem will lead to a follow-up, moredetailed analysis using more accurate tools and input data. They are also well-suited to performance management applications involving LOS or capacity calculations (e.g., calculating the number of miles of state highway operating at LOS E or worse during peak periods). They are not suitable for making final decisions about roadway design or control elements, nor for making final assessments about the adequacy of a roadway to accommodate additional demand (such as might be done as part of a traffic impact study). Availability of a suitable table. The accuracy of the results from a generalized service volume table depends greatly on how well the default values used to generate the table match the conditions on the roadway being analyzed. Section B3 discusses potential sources of service volume tables and their respective advantages and disadvantages. Assumptions common to any service volume table include: (1) uniform roadway cross-section, (2) uniform roadway demand, (3) no queue spillback (e.g., from a left-turn lane, from an off-ramp, from one freeway segment to another), and (4) traffic signal timing that adequately accommodates all turning movements (HCM 2010, Florida DOT 2013). The more that actual conditions vary from these assumptions, the less suitable a service volume table will be. Local policy. State and local transportation agencies traffic analysis guidelines may specify that a particular service volume table should be used for particular types of analyses, or that service volume tables should not be used in particular circumstances. One should also be cautious when the estimated LOS is near or at LOS F. The actual operations of the intersection, segment, or facility fluctuate a great deal at the LOS E/F boundary. Consequently, service volume tables cannot be relied upon when approaching this boundary. More detailed analyses are required to better pinpoint the actual operations. Sources of Generalized Service Volume Tables There are three main sources for generalized service volume tables, which are discussed in more detail in the remainder of this section: 1. The HCM s generalized service volume tables, 2. Florida DOT s generalized service volume tables, and 3. Local service volume tables. HCM Generalized Service Volume Tables The HCM 2010 provides generalized service volume tables for the following system elements: Freeway facilities (Chapter 10, Exhibits 10-8 and 10-9), 45

46 Multilane highways (Chapter 14, Exhibits and 14-19), Two-lane highways (Chapter 15, Exhibit 15-30), Urban street facilities (Chapter 16, Exhibit 16-14), and Signalized intersections (Chapter 31, Exhibit 31-69). Assumptions (e.g., default values) used to develop the tables are provided with each table and explained in the accompanying text in the HCM The default values used to develop the tables are based on the HCM s national average values, which may be different from local conditions in the area being analyzed. In particular, the default values for percent heavy vehicles, peak hour factor, free-flow speed, and (for urban streets) through traffic g/c ratio (the percentage of time through traffic receives a green signal at a traffic light) and traffic signal spacing are recommended to be compared to local conditions, if possible, when evaluating the suitability of the HCM tables for a particular analysis. Except for the signalized intersection table, all of the HCM s tables are daily tables (i.e., they present maximum AADTs for a given LOS) and the user must provide select appropriate K- (analysis hour) and D- (directional) factors that convert AADT to an analysis hour directional volume when applying the table. The signalized intersection table presents maximum hourly volumes for a given LOS; users can convert these to AADTs by applying K- and D-factors. Other inputs required by the HCM tables are: Number of travel lanes, Terrain type (uninterrupted-flow facilities), Area type (freeways and multilane highways), Highway class (two-lane highways), Posted speed (urban streets), and g/c ratio (signalized intersections). FDOT Generalized Service Volume Tables The Florida DOT (FDOT) is one of the leading users of generalized service volume tables and has sponsored a considerable body of research related to them. FDOT s Quality/Level of Service Handbook (2013) describes the assumptions and methodological extensions used in developing the FDOT tables; the tables themselves also list the input values used to develop them. The default values used by FDOT s tables are based on typical Florida values, which may be different from conditions in other locations. In particular, the daily Florida tables use default K- and D-factors that are representative of Florida conditions, but are recommended to be compared to local conditions when the tables are considered for use elsewhere. As with the HCM tables, key default values that can significantly affect results are recommended to be compared to local conditions if possible; these 46

47 include percent heavy vehicles, peak hour factor, free-flow speed, and (for urban streets) through traffic g/c ratio, saturation flow rate, and traffic signal spacing. Finally, the FDOT tables assume level terrain. Both daily and peak-hour service volume tables are provided for the following facility types and modes: Signalized arterial streets, Freeways, Uninterrupted-flow highways (multilane and two-lane highways use the same table), and Bicycles on urban streets, Pedestrians on urban streets, and Buses on urban streets. Input data required by these tables consists of: Signalized arterials: state or non-state roadway, number of lanes, posted speed, median type, presence of exclusive left- and right-turn lanes, and one- or two-way facility Freeways: number of lanes, auxiliary lane presence, ramp meter usage Uninterrupted-flow highways: number of lanes, median type, presence of exclusive left-turn lanes, passing lane percentage (two-lane highways only) Bicycles: percent of facility with a paved shoulder or bicycle lane (three categories corresponding to nearly all, more than half, less than half) Pedestrians: percent of facility with a sidewalk (same categories for as bicycles) Buses: percent of facility with a sidewalk (nearly all, all others), bus frequency Although FDOT uses the HCM as the starting point for the computations used to develop its tables, there are some important differences in the methodologies that mean that the FDOT tables will produce different results than a pure application of the HCM method. Key differences include: Signalized arterials: methodological extension for auxiliary lanes through intersections, use of arterial classes for determining LOS thresholds Freeways: treatment of capacity reductions in interchange areas, maximum capacity values for different area types, methodological extension for ramp metering effects Uninterrupted-flow highways: methodological extension for left-turn lane provision, FDOT uses a different two-lane highway method than the HCM Bicycles and pedestrians: The FDOT methods, while using similar inputs, uses different computations than the HCM methods. Buses: The FDOT method is adapted from the Transit Capacity and Quality of Service Manual (TCQSM) 2nd Edition (Kittelson & Associates et al. 2003), while the HCM and the TCQSM 3rd 47

48 Edition (Kittelson & Associates et al. 2013) use a different method that consider some of the same factors. Local Service Volume Tables Developing local service volume tables is a way to address a key issue with applying service volume tables namely, that the assumptions used to develop the tables may not necessarily match local conditions. In addition, local service volume tables can be developed that allow the user to vary other parameters than those used by the HCM or FDOT tables. The effort taken to develop local tables can pay off with the creation of an easy-to-apply that produces reasonable results. Appendix B of Chapter 6 in the HCM 2010 describes a method for developing local service volume tables. The analyst needs to develop a default value for each input parameter used by the applicable HCM method. When the HCM method is particularly sensitive to a particular parameter, or when the range of local observed values varies greatly, a set of default values should be considered for that parameter. Section A provides guidance on selecting appropriate default values. Once the default values are selected, the analyst uses a computational engine or HCM-implementing software to back-solve for the maximum volume associated with a particular LOS, using the analyst s selected set of default values (HCM 2010). As an alternative, FDOT s LOSPLAN planning software package provides table generators that build service volume tables from a set of user-specified input values (Florida DOT 2013). The user should be aware of the differences between the FDOT and HCM methods, highlighted above, before applying these service volume table generators. References Florida Department of Transportation Quality/Level of Service Handbook. Tallahassee, Highway Capacity Manual Transportation Research Board, National Research Council, Washington, D.C., Highway Capacity Manual Transportation Research Board of the National Academies, Washington, D.C., Kittelson & Associates, Inc.; KFH Group, Inc.; Parsons Brinckerhoff Quade and Douglass, Inc.; and K. Hunter-Zaworski. TCRP Report 100: Transit Capacity and Quality of Service Manual, 2nd Edition. Transportation Research Board of the National Academies, Washington, D.C., Kittelson & Associates, Inc.; Parsons Brinckerhoff; KFH Group, Inc.; and Texas A&M Transportation Institute. TCRP Report 165: Transit Capacity and Quality of Service Manual, 3rd Edition. Transportation Research Board of the National Academies, Washington, D.C.,

49 PART II MID-LEVEL ANALYSIS METHODS The chapters in this part of the Guide describe mid-level analysis methods are work best when evaluating a single freeway, highway, or urban street facility composed of several segments, interchanges, and intersections. This part also provides some quick estimation procedures for use in scoping and screening planning and preliminary engineering analyses at the mid-level. The methods described here provide a macroscopic level of detail on facility performance and multimodal level of service. 49

50 CHAPTER 8 FREEWAY ANALYSES 1. INTRODUCTION A freeway is a grade separated highway with full control of access and two or more lanes in each direction dedicated to the exclusive use of motorized vehicles. This chapter presents mid-level methods suitable for evaluating single freeway facilities or segments 2. APPLICATIONS The methodologies presented in this chapter support the following planning and preliminary engineering applications: Development of a freeway corridor system management and improvement plan. Feasibility Studies of: o Adding an HOV, HOT, or express lane (or convert an existing lane or shoulder lane to HOV, HOT, or toll operation); o Ramp metering; o Managed lanes, including speed harmonization, temporary shoulder use, and other active transportation and demand management (ATDM) strategies. An interchange justification or modification study (the freeway mainline portions of these studies). Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW Freeway performance can be directly measured in the field or it can be estimated in great detail using microsimulation. However the resource requirements of both of these methods render them generally impractical for most planning and preliminary engineering applications. The HCM provides a less resource intensive approach to estimating freeway performance, however; it also is generally impractical to use the HCM with 100% field measured inputs for many planning and preliminary engineering analyses. This chapter presents 2 mid-level methods for evaluating freeway performance plus a high level screening/scoping method that can be used to focus the analysis on only those locations and time periods requiring investigation (see Exhibit 13). The HCM segment and facility analysis methods (covered in Chapters 10 to 13 of the HCM 2010) provide a good basis for estimating freeway performance under many conditions. The basic segment analysis method is relatively simple to apply when defaults are used for some difficult to obtain inputs. Analysis of weaving segments and ramp merge/diverge segments is a bit more challenging with a more complex 50

51 set of equations, but computational effort is simplified with software. The freeway facility method is the most challenging requiring a great deal more data to cover the larger geographic area involved in a full facility analysis and several computations are iterative. Generally, specialized software is required to implement the HCM facility method. A simplified HCM facility analysis method is consequently presented in this chapter to reduce the number of computations and eliminate the dynamic typing of segments and the iterative nature of the computations. The simplified analysis method is designed to be easily programmable in a static spreadsheet without requiring writing any visual basic code to implement it. Exhibit 13: Analysis Options for Freeways Because the HCM method and the simplified method both require a fair amount of data, this chapter also provides a high level service volume and v/c ratio screening method for quickly identifying which portions of the freeway can be evaluated solely using the segment analysis methods, which portions will require a facility level analysis (to properly account for the spillover effects of congestion), and to quickly compare improvement alternatives according to the capacity they provide. 4. SCOPING AND SCREENING METHOD Whether or not a more detailed freeway facility analysis is needed can be determined by comparing the counted or forecasted peak hour or daily traffic volumes for the sections of the freeway between each on and off-ramp to the values given in Exhibit 14. If all of the section volumes fall in the level of service E range or better, there will not be congestion spill over requiring a full facility analysis to better quantify the performance of the facility. One can then use the HCM segment analysis procedures with defaults for some of the inputs to evaluate the performance of each segment. (Note that segments have a special definition in the HCM, while sections are defined in this Guide by the freeway on and off-ramps.) 51

52 The service volumes in Exhibit 14 can also be used to quickly determine the geographic and temporal extent of the freeway facility that will require analysis. If the counted or forecasted volumes for a section fall below the agency s target LOS standard, then the section can be excluded from a more detailed analysis. Any section that exceeds the capacity values in Exhibit 14 will have queuing that may impact upstream sections and reduce downstream demands. In such a situation a full freeway facility analysis is required to ascertain the performance of the freeway. The facility analysis can be performed either using the HCM method with defaults, or the simplified HCM method. Both of which are described later in this chapter. The analyst may also use the capacities in Exhibit 14 to compute the peak hour, peak direction demand/capacity ratio for each segment under various improvement options. The options can then be quickly ranked according to their forecasted demand/capacity ratios for the critical sections of the freeway. Estimating Freeway Service Volumes The approximate maximum average annual daily traffic (AADT) (two-way) that can be accommodated by a freeway at a given level of service can be estimated from Exhibit 14. For example, an 8-lane freeway can carry between 104,000 (13,000 x 8 lanes) and 160,000 (20,000 x 8 lanes) AADT at LOS E, depending on its location (urban or rural) and the terrain type. Higher AADT s can be accommodated at lower K (peak hour proportion) and D (directional proportion) factors. Exhibit 14: Daily and Peak Hour Service Volume and Capacity Table for Freeways Peak Hour Peak Direction (veh/h/ln) AADT (2way veh/day/2way ln) Type Terrain LOS E LOS E LOS A-C LOS D LOS A-C LOS D (capacity) (capacity) Urban Level ,000 17,400 20,200 Urban Rolling ,300 16,600 19,200 Rural Level ,300 12,400 14,100 Rural Rolling ,300 11,200 12,700 Notes: - Entries are maximum vehicle volumes per lane that can be accommodated at stated level of service (LOS). - AADT = annual average daily traffic. AADT/lane is two-way AADT divided by sum of lanes in both directions. - Urban area assumptions: Free-flow speed = 65 mph, 5% trucks, 0% buses, 0% RVs, 0.95 PHF, 3 ramps/mi, driver population factor = 1.00, 12-ft lanes, k factor = 0.09 for urban, 0.10 for rural; D factor = Rural area assumptions: Free-flow speed = 65 mph, 12% trucks, 0% buses, 0% RVs, 0.88 PHF, 0.2 ramps/mi, Driver population factor = 0.85, 12-ft lanes, 6 ft lateral clearance, K factor = 0.10; D factor = Values can be adjusted for other assumptions. - K factor is the ratio of weekday peak hour two-way traffic to AADT. - D-factor is the ratio of peak direction traffic to both directions peak hour traffic. - Adapted from Exhibit 10-8 and Exhibit 10-9 of HCM

53 Single lane managed lanes (HOV lanes, HOT lanes, etc.) have capacities between 1500 and 1800 veh/hr/ln depending on the free-flow speed and the type of barrier or buffer (if any) separating the single managed lane from the other mixed flow lanes. Dual managed lanes have capacities between 1650 and 2100 veh/hr/ln (Exhibit HCM 2010 Update unpublished Draft). When local traffic data suggests that other values for the assumptions than those noted in Exhibit 14 would be more appropriate, the analyst should modify the daily and hourly service volumes using HCM 2010 Equation 10-5 adapted as shown below: DSV = DSV 0 f HV f p PHF K D Where: DSV DSV 0 f HV, f HV,0 f p, f p,0 PHF, PHF 0 K, K 0 D, D 0 K 0 D 0 f HV,0 f p,0 PHF 0 Equation 1 = daily service volume (veh/day/ln) = initial daily service volume in Exhibit 14 (veh/day/ln) = desired and initial adjustment factor for presence of heavy vehicles in traffic stream. = desired and initial adjustment factor for unfamiliar driver populations. = desired and initial peak-hour factor. = desired and initial proportion of daily traffic occurring in the peak hour of the day. = desired and initial proportion of traffic in the peak direction during the peak hour. The same equation can be used to modify the peak hour peak direction service volumes if the initial peak hour service volumes from Exhibit 14 are used instead of the daily values. Daily service volumes should be rounded to the nearest thousand vehicles, given the many default values used in their computation. Peak hour, peak direction service volumes should be rounded to the nearest ten vehicles. 53

54 5. EMPLOYING THE HCM WITH DEFAULTS The HCM divides the freeway facility into various uniform segments that may be analyzed to determine capacity and level of service (LOS). Chapter 10 of the 2010 HCM provides more details on how each segment type is defined. HCM Data Needs and Defaults Exhibit 17 lists the data needed to evaluate the full range of performance measures for freeway facility and segment analysis. Individual performance measures may require only a subset of these inputs. Exhibit 15: Required Data for HCM Freeway Analysis Required to Estimate Input Data (units) FFS Cap Spd LOS Que Rel Comments/Defaults Lane widths and right side 12 ft lanes lateral clearance (ft) 6 ft lateral clearance Ramp density (per mile) Must be provided Percent heavy vehicles (%) 10% (rural), 5% (urban) Terrain type/specific grade Must be provided Number of directional lanes Must be provided Peak hour factor (decimal) 0.88 (rural), 0.95 (urban) Driver pop factor (decimal) 1.00 Segment length (mi) Must be provided Directional demand (veh/h) Must be provided Variability of demand Must be provided Incident/Crash frequencies Must be provided Weather frequencies Must be provided Work zone frequencies Must be provided *We need to double check the defaults R.Dowling Notes: - FFS = free-flow speed (default = speed limit plus 5 mi/h) - Cap = Capacity (veh/hr/ln) - Spd = Speed (mi/h) - LOS = level of service (If service volume table used, only AADT, K, D, and number of lanes are required) - Que = Queue (veh) - Rel = Travel Time Reliability The estimation of free-flow speeds using the HCM requires information on the facility geometry (lane widths, right side lateral clearance and the density of ramps). Capacity (in terms of vehicles per hour) requires the free-flow speed plus additional data on heavy vehicles, terrain type, number of lanes, the peak hour factor (the ratio of the average hourly flow to the peak 15 minute flow rate), and the driver population factor (an adjustment to reduce capacity to reflect the effects of unfamiliar drivers). 54

55 Once the free-flow speed and capacity have been calculated in the HCM then speed, level of service (LOS), and queues can be estimated with additional information on the segment lengths and the directional demand (vehicles per hour). Reliability requires the same data as required to estimate speeds plus information on the variability of demand; the severity, frequencies and durations of incidents; the frequency of adverse weather; and the frequencies of work zones by number of lanes closed by duration. 55

56 6. SIMPLIFIED HCM FACILITY METHOD The simplified HCM facility method for freeways focuses on facility level analysis and section level analysis. A section is defined as extending from gore point to gore point, avoiding the need to subdivide the section into 1500 foot long merge and diverge areas. A section may combine several HCM segments. For example, a section extending between and on-ramp and an off-ramp may be composed of 3 HCM segments: a merge segment, a basic or weave segment, and a diverge segment. Definition of Sections for Simplified Method Input variables are characterized into global and section inputs. Rather than having to go through the tedious and involved process of HCM facility segmentation, in a planning analysis we define sections to occur between points where either demand or capacity changes. For example, if a lane drop exists between an on- and off-ramp that length will involve two sections (because the reduced number of lanes reduces the capacity of the section). But for a three-segment sequence of merge area, basic segment, and diverge area, the proposed methodology defines a single section. This facilitates and simplifies user input, and is more compatible with travel demand model links, as well as modern data sources on travel time. For example, a facility with 11 segments as is shown in Example Problem 1 of the HCM2010, would be transformed into a facility with seven sections in the planning application (see Exhibit 16). Exhibit 16: Schematic of HCM Segment to Simplified HCM Method Section Data Needs The data needs for the simplified HCM facility analysis method (shown in Exhibit 17) are similar to those of the HCM method listed in the previous exhibit. The differences are that the simplified method uses posted speed limits to estimate the free flow speed (rather than lane widths, lateral clearance, and ramp density) and the reliability analysis in the simplified method requires only the crash rate for the facility (rather than the variability of demand, incident rate, and weather frequencies). Global inputs include information about the facility of interest. Those are applied to all sections across all analysis periods. They include free flow speed (S FFS ), peak hour factor (PHF), percent heavy vehicles (%HV), k factor (to convert annual directional AADT to hourly flow rates), and a traffic growth factor (if used to obtain forecasts). 56

57 Exhibit 17: Required Data for Simplified Freeway Facility Analysis Required to Estimate Input Data (units) FFS Cap Spd LOS Que Rel Comments/Defaults Posted Speed Limit (mi/h) Must be provided Percent heavy vehicles (%) 10% (rural), 5% (urban) Terrain type/specific grade Must be provided Number of directional lanes Must be provided Peak hour factor (decimal) 0.88 (rural), 0.95 (urban) Driver pop factor (decimal) 1.00 Segment length (mi) Must be provided Directional demand (veh/h) Must be provided Average crash rate Must be provided *We need to double check the defaults. R. Dowling Notes: - FFS = free-flow speed (default = speed limit plus 5 mi/h) - Cap = Capacity (veh/hr/ln) - Spd = Speed (mi/h) - LOS = level of service (If service volume table used, only AADT, K, D, and number of lanes are required) - Que = Queue (veh) - Rel = Travel Time Reliability Estimation of Inputs This section describes procedures for estimating the free-flow speed, the section type, and the section capacities Identifying Freeway Section Types The following definitions are used to split the freeway mainline into its component sections: - A basic freeway section is a section of freeway with a constant demand and capacity, without the presence of on-ramps or off-ramps - A freeway ramp section is a section of freeway with an on-ramp, off-ramp, or both, but without the presence of auxiliary lanes to connect two ramps, - A freeway weaving section occurs wherever an on-ramp is followed by an off-ramp, and the two are connected by an auxiliary lane. Estimating Free-Flow Speed The most accurate method for estimating segment free-flow speeds is to measure it in the field during low flow (under 800 veh/hr/ln) 2. In urban environments, traffic sensors may be available to allow the estimation of free-flow speeds, however for planning applications this is not usually practical. The HCM provides an equation for estimating free-flow speeds based on facility geometry. 3 2 Adapted from Exhibit 11-3, HCM 2010, accounting for likely peak hour factor and heavy vehicle effects. 3 Souce: equation 11-1, HCM

58 FFS = f LW f LC 3. 22TRD 0.84 Equation 8 Where: - FFS = free-flow speed (mi/h) - f LW = adjustment for lane width (mi/h) o (0.0 for 12 foot or greater lanes, 1.9 for 11 foot lanes, 6.6 for 10 foot lanes) (see exhibit 11-8, HCM 2010 for details) - f LC = adjustment for right side lateral clearance (mi/h) o ranges from zero for 6 foot lateral clearance to 3.0 for one foot lateral clearance on a 2 directional lane freeway (see Exhibit 11-9, HCM 2010 for details). - TRD = total ramp density (ramps/mi) o Number of on and off-ramps in one direction for 3 miles upstream and 3 miles downstream, divided by 6 miles. An alternate approach is to assume the free-flow speed (the average speed of traffic under low flow conditions) is equal to the posted speed limit plus an adjustment reflecting local driving behavior. Florida adds 5 mi/h to the posted speed limit. Estimating Section Capacities Free flow speed and percent heavy vehicles are used to calculate section capacity using the following equation: Where: c i = (2, (min(70, S FFS) 50)) CAF 1 + %HV/100 Equation 9 Ci = capacity of section I (vph/ln) S FFS = Free-flow speed (mph) %HV = percent of heavy vehicles (trucks with more than 6 tires, buses, and recreational vehicles in traffic stream (see Exhibit 17 for suggested default). CAF = a capacity adjustment factor that is used to calibrate the basic section capacity given in the HCM to account for influences of ramps, weaves, or other impacts. The equation is fully consistent with the HCM 2010 speed flow models. Section inputs include section type (Basic, Weave, Ramp), section length (mi), section number of lanes, and section directional AADT. This information, together with the global inputs are used to calculate free flow travel rate (the inverse of free flow speed), capacity adjustment factors for weave and ramp sections, adjusted lane capacity (the product of base capacity and CAF), and section capacity (the product of adjusted lane capacity and number of lanes). 58

59 Assigning Section Demands Generally, daily or peak hour demands are required for each segment of the freeway facility. These are then converted to 15-minute demands for each section, with unserved demand from a prior 15 minute period, carried over to the following 15 minute period. The demand level for each section is determined from entering demand, exiting demand, and carry-over demand from a previous analysis period (in the case of oversaturation). From this, the demand-tocapacity ratio is calculated, and the delay rate is computed as discussed later. For each section and time period, the method further estimates travel rate, travel time, density per lane, and segment queue length. Using AADT i on section i, k-factor, traffic growth factor (f g ), and peak hour factor (PHF), section in-flow and out-flow during time period t, q i,t are computed as follows: q i,t = AADT i k f g AADT i k ( 1 PHF ) f g AADT i k f g { AADT i k (2 1 PHF ) f g t = 1 t = 2 t = 3 t = 4 Equation 10 Where: q i,t is in or out flow for section i at analysis period t, AADT i is AADT for section i, f g is the growth factor, and all other parameters are defined previously. The demand level d i,t in section i at time t is computed as the demand level in section i 1 plus the inflow at section i at time t minus the out-flow at the same section at time t, plus any carry over demand in section i at the previous time interval t 1. The relationship is as shown below: d i,t 1 The carry over demand d i,t capacity as follows: d i,t = d i 1,t + (q i,t ) in (q i,t ) out + d i,t 1 Equation 11 at section i at time t is the difference between the section demand and 59

60 d i,t = max(d i,t c i, 0) Equation 12 The carry over demand is also used as an indication of the presence of a queue on the section. Note that queues are considered to be vertical, and are not carried to an upstream link. Section queue length is estimated by dividing the difference in lane demand and capacity by its density. It essentially provides an estimate for how long the queue would spillback at the given density, assuming a fixed number of lanes upstream of the bottleneck. Estimating Section Volume/Capacity Ratios The section volume/capacity ratios are then computed using the section demands and capacities previously computed. Speed Segment speeds are estimated based on delay rate curves. The estimated delay is added to the estimated travel time at free-flow speed to obtain the travel time with congestion effects. The congested travel time is divided into the segment length to obtain the average speed. Estimating Section Delay Rates In the following, details for the delay rate estimation are presented for basic sections without the influence of on-ramps or off-ramps. That discussion is followed by recommended adjustments for merge, diverge, and weaving segments. Basic Section The proposed approach is based on estimating delay rate per unit distance as a function of section demand-to-capacity ratio. The delay rate is calculated as the difference between actual and free-flow travel time per unit distance. The calculation of the delay rate needs to be performed separately for undersaturated and oversaturated flow conditions. Undersaturated Flow Conditions For undersaturated flow conditions, the 2010 HCM basic segment speed-flow model is used to estimate delay rates. For undersaturated flow conditions a two-regime model was developed for each free flow speed as shown in Equation 13 and Exhibit 18: Equation 13 0 RUi,t = { A ( d i,t ) 3 + B ( d i,t ) 2 + C ( d i,t ) + D c i c i c i d i,t c i E d i,t c i < E 1 Where: 60

61 RUi,t is the delay rate for undersaturated segment i at time t. di,t is demand for segment i at time t, ci is segment capacity, Where the values of parameters A, B, C, D, and E are shown in Exhibit 18, based on segment FFS, the basic segment speed-flow relationships and all other parameters are defined previously. Exhibit 18: Values for the Parameters of Equation 6 FFS (mph) A B C D E For each FFS, the sole input to the regression model is the demand-to-capacity ratio. The undersaturated model is applied up to a demand-to-capacity ratio of 1.05 to avoid a discontinuity with the oversaturated model described below. Oversaturated Flow Conditions For oversaturated flow conditions, the delay rate is approximated assuming uniform arrival and departures at a freeway bottleneck. The additional oversaturation delay rate is calculated using the following equation Where: RO i,t = T ( d i,t 1) 2L i c i Equation 14 RO i,t is the additional average delay rate due to oversaturation for segment i at time t. (s/mi) T is the analysis period duration (typically 900 seconds)(s) Li is the length of the segment (mi) di,t is demand for segment i at time t (veh/h) ci is segment capacity (veh/h), 61

62 After determining the delay rate, the travel rate is determined by summing up the value of delay rate and travel rate under free flow conditions. The section travel time is then computed by multiplying the travel rate and segment length. Where: T i = 3600L i FFS i + L i ( RUi,t + RO i,t ) T i is the segment travel time (s) L i is the length of the segment (mi) FFS i is the segment free-flow speed (mi/h) RUi,t is the delay rate for undersaturated segment i at time t. RO i,t Equation 15 is the additional average delay rate due to oversaturation for segment i at time t. (s/mi) Adjustments for Weave Section As mentioned above, the recommended approach is focused on the basic freeway segment speed-flow model to estimate delay rate and travel speed on a section. When applied to weave sections, a capacity adjustment factor is required to account for the generally lower capacity in weaving segments compared to basic segments. With that adjusted capacity, the basic segment planning method can be applied to weaving segments. The proposed model is as follows: CAF weave = V r L s Equation 16 Where: CAF weave is the capacity adjustment factor used for a weaving segment (CAF weave 1.0) V r is the ratio of weaving demand flow rate to total demand flow rate in the weaving segment, and L s is length of the weaving segment (ft). Adjustments for Merge and Diverge Sections Merge Sections As mentioned before, the approach used is to generate an equivalent merge or diverge segment capacity that would yield speeds that were equivalent to a basic segment speed. An average CAF value of 0.95 for all merge segments should be used regardless of configuration. In application of the method, 62

63 user-specific calibration of that CAF is possible and recommended for merge segments with known capacity constraints and congestion impacts. Diverge Sections For diverge segments an average CAF value of 0.97 is recommended. Again, user-specific calibration of this factor is encouraged. Ramp Section Capacity Calculation The overall capacity of ramp sections is determined from a length-weighted average of the capacity of the merge, basic, and diverge segments within a given section. It is noted that the effective length of merge and diverge segments are 1500 ft each in the HCM. If the section is shorter than 3000 ft, the length of the basic freeway segment is considered zero and the length of the merge and diverge segments is assumed to each be equal to half of the section length. Computing Speed At this stage, the methodology determines travel rate at section i at time t by adding the associated travel rate under free flow conditions TR FFS and delay rate R i,t. It then calculates travel time TT i,t by multiplying the travel rate by section length L i : TR i,t = R i,t + TR FFS Equation 17 TT i,t = TR i,t L i The average speed S i,t in section i at time t is found as follows: Equation 18 S i,t = L i TT i,t Equation 19 Level of Service The facility-wide average density is computed and then the LOS grade is determined from a look up table. The density D i,t of section i at time t is found by dividing section demand d i,t = d i,t by its speed S i,t as follows: 63

64 D i,t = d i,t S i,t Equation 20 This mixed vehicle density is converted to passenger cars using the equation below: D D PC = PHF x f HV x f P Equation 21 Where: D = mixed vehicle density (veh/mi/ln) D PC = passenger car density (pc/mi/ln) PHF = Peak hour factor (see Exhibit 17 for recommended defaults) F HV = heavy vehicle factor 1 = 1+P t (E HV 1) Where: P t = Percent Heavy Vehicles (see Exhibit 17 for recommended percent defaults) E HV = passenger car equivalent for heavy vehicles (1.5 for level terrain, 2.5 for rolling terrain. See Exhibit HCM 2010 for other options). F P = driver population factor (see Exhibit 17 for recommended default). The segment densities are averaged weighted by lanes and length to obtain the average density for the facility. Where: D F = D ixl i xn i L i xn i D F = facility average passenger car density (pc/mi/ln) D i = Segment I passenger car density (pc/mi/ln) L i = Length of segment (mi) N i = Number of lanes in segment Equation 22 The facility and segment passenger car densities are entered into Exhibit 19 to obtain the level of service. 64

65 Exhibit 19: LOS Criteria for Freeway Facilities Average Facility or Section Density Level of Service (pc/mi/ln) A <= 11 B >11-18 C >18-26 D >26-35 E >35-45 >45pc/mi/ln F or any section has v/c>1.00 Adapted from Exhibit 10-7, HCM Queues A segment is considered to be in 100% queue if its estimated density is greater than 45 passenger car equivalents per lane per mile. For segments with densities below 45 and d/c greater than 1.00, then the section queue length is estimated by dividing the difference in lane demand and capacity by its density. It essentially provides an estimate for how long the queue would spillback at the given density, assuming a fixed number of lanes upstream of the bottleneck. Where: QL i = queue length in segment I at time t. d i,t = demand on segment I at time t. c i = capacity of segment i D i,t = Density on segment I at time t. QL i,t = max(d i,t c i, 0) D i,i Equation 23 65

66 7. RELIABILITY The travel time on a facility will vary from hour to hour, day to day, season by season of the year, depending on fluctuations in demand, weather, incidents, and work zones. Reliability measures are an attempt to characterize this distribution of travel times for a selected period (often the non-holiday, weekday AM or PM peak period) of a year in some way meaningful to the analyst, the agency s objectives, and the general public. Exhibit 20 shows two measures (The 95 th percentile travel time index and the percent of trips less than 45 mph) of many possible measures for characterizing the travel time distribution and communicating travel time reliability to decision makers and the public. The agency and the analyst may choose other measures or other thresholds (such as the 85 th percentile travel time index) for characterizing reliability. The HCM 2010 provides a relatively data and computationally intensive method for evaluating freeway reliability. The Florida DOT has developed a reliability analysis procedure as well [4]. Both methods provide defaults for many of the required inputs, but both require custom software to apply. HCM Method Using Defaults The HCM method for estimating travel time reliability is described in Chapters 36 and 37 of the 2010 HCM. Exhibit 21 lists the required input and points to where defaults are available in Chapter 36. Exhibit 20: Characterizing Travel Time Reliability 66

67 Exhibit 21: Input Data Needs for HCM Reliability Analysis of Freeways Data Category Description Defaults Time Periods Analysis period, study period, Must be selected by analyst. reliability reporting period. Demand Patterns Day-of-week by month-of-year Defaults provided in Chapter 36 demand factors. Weather Probabilities of various intensities of rain, snow, cold, and low visibility by month. Data sources and defaults provided in Chapter 36 Incidents Work Zones, Special Events Crash rate and incident-to-crash ratio for the facility, in combination with defaulted incident type probability and duration data. Changes to base conditions and schedule. Crash rate must be provided. Defaults available in Chapter 36 for other data. Must be provided, if any. Nearest City City with airport weather station Required to look up weather Traffic Counts Demand multiplier for demand represented in base dataset Must be provided. Adapted from Exhibit 36-2, HCM Simplified Method The following equations adapted from SHRP2-C11 can be used to estimate freeway facility reliability.[3] [4] First the average annual travel time rate (hours/mile) including incident effects is computed: TTI m = 1 + FFS (RDR + IDR) Equation 24 Where: TTI m = average annual mean travel time index (unitless) FFS = free-flow speed (mi/h) RDR = Recurring delay rate (h/mi) IDR = Incident Delay Rate (h/mi) RDR = 1 S 1 FFS Equation 25 IDR = { (N 2) } X 12 Equation 26 Where S = peak hour speed (mi/h) N = number of lanes in one direction (N = 2 to 4) X = peak hour volume/capacity ratio Note: IDR equation is valid for X <=

68 The 95 th percentile travel time index (TTI 95 ) and percent of trips traveling at under 45 mi/h (PT 45 ) then can be computed from the average annual travel time index according to the following equations. TTI 95 = ln (TTI m ) Equation 27 PT 45 = 1 exp ( (TTI m 1)) Equation 28 where TTI 95 = the 95th percentile TTI; PT 45 = the percent of trips that occur at speeds less than 45 mi/h 8. ADAPTATIONS FOR ADVANCED FREEWAY MANAGEMENT PRACTICES Although much remains unsettled as to the precise impacts of advanced freeway management practices on freeway capacities and speeds, there is some research on some practices that can be summarized here. Ramp metering Ramp metering can result in more efficient merging at the ramp merge. Research by Zhang and Levinson [9] suggests that ramp metering can increase freeway mainline bottleneck capacity by 2% to 3% by smoothing out demand surges. HOV/HOT lanes Single lane high occupancy vehicle (HOV) and high occupancy toll (HOT) lanes restrict the ability of eligible vehicles to pass each other. Thus capacities are somewhat lower that for the equivalent mixed flow lanes on the freeway, depending on how the HOV/HOT lane is separated from the rest of the lanes on the freeway. NCHRP Web-Only Document 191 [8] suggests that capacities on the order of 1600 to 1700 vehicles per hour per lane may be appropriate for single HOV/HOT lanes. Temporary shoulder use Temporary shoulder use opens the shoulder lane to traffic for limited periods each day. Tentative data suggests that the capacity and speed on a temporary shoulder lane are lower than for the adjacent full time lanes. Speed harmonization Variable speed limit and speed harmonization installations are intended to give drivers advance notice of downstream slowing and to provide recommended speeds for upstream drivers to reduce the shockwaves on freeways. These installations are intended to improve safety and reduce the effects of primary incidents on freeway operations. The magnitudes of these effects depend on the specifics of their installation. This topic is currently the subject of FHWA research, and at this time it is not clear what the precise effects would be. 68

69 Autonomous & connected vehicles Autonomous and connected vehicles have the potential to increase or decrease freeway capacities and speeds, depending on the specifics of their implementation. This topic is currently the subject of FHWA research and it is not clear at this time what their effects would be. 9. MULTIMODAL LOS The 2010 HCM does not provide LOS measures for trucks, transit, bicycles, and pedestrians on a freeway facility. See Chapter 15 Pedestrians, Bicyclists, and Public Transit and Chapter 16 Truck Level of Service for guidance on evaluating multimodal LOS on freeways. 10. EXAMPLE An example application of the simplified freeway facility method is shown in Part IV, case study I. 11. REFERENCES 1. Burr, I. (1942). Cumulative frequency functions. Annals of Mathematical Statistics, 13, Dowling, R., G. List, B. Yang, E. Witzke, A. Flannery, Final Report, NCFRP Project 41, Incorporating Truck Analysis into the Highway Capacity Manual, Transportation Research Board, Washington, DC, Economic Development Research Group, et al., SHRP2-C11 Final Report, Development of Tools for Assessing Wider Economic Benefits of Transportation, Report S2-C11-RW-1, Transportation Research Board, Washington, DC, Elefteriadou, L., Lu, C., Li, Z., Wang, X., Jin, L., FINAL REPORT to THE FLORIDA DEPARTMENT OF TRANSPORTATION SYSTEMS PLANNING OFFICE on Project Multimodal and Corridor Applications of Travel Time Reliability FDOT Contract BDK , University of Florida, Gainesville, FL, March 30, Source for Incident Delay Rate: equation fitted to Table B.2.14 IDAS User s Manual, accessed August 14, Taylor, M. A., & Susilawati. (2012). Using The Burr Distribution For Measuring Travel Time Reliability. Proceedings of the 5th International Symposium on Transportation Network Reliability. Hong Kong, China. 7. Federal Register. (2013, February). Federal Register, 78(25), Wang, Yinhai; Xiaoyue Liu, Nagui Rouphail, bastian Schroeder, Yafeng Yin, Loren Bloomberg, Analysis of Managed lanes on Freeway Facilities, NCHRP Web Only Document 191, Transportation Research Board, Washington, DC, Zhang, Lei; D. Levinson, Ramp Metering and Freeway Bottleneck Capacity, Transportation Research Part A, Elsevier Ltd, New York, New York, v44, 2010, pp

70 CHAPTER 9 MULTILANE HIGHWAYS 1. INTRODUCTION Multilane highways are roadways with a minimum of two lanes in each direction with traffic signal, stop, or roundabout intersection controls nor more frequently than 2 miles apart. They have no access control or partial control of access. This chapter presents midlevel methods for evaluating single multilane highway sections and facilities. 2. APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Development of a highway corridor improvement plan. Assessment of the impact on facility operations of changing or adding more intersection controls. Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW The HCM provides a method for estimating the performance of multilane highway sections in between intersections. It does not provide a method or level of service measures for evaluating multilane highway facilities, combining the operations of sections with signalized, stop, or roundabout controlled intersections. This chapter presents: 1. A high level screening/scoping method that can be used to focus the analysis on only those locations and time periods requiring investigation (see Exhibit 22). 2. The HCM mid-level method for evaluating multilane highway section performance using defaults. 3. A mid-level procedure for combining intersection and section performance into estimating multilane facility performance. 70

71 Exhibit 22: Analysis Options for Multilane Highways 4. SCOPING AND SCREENING METHOD Whether or not a more detailed multilane highway analysis is needed can be determined by comparing the counted or forecasted peak hour or daily traffic volumes for the sections of the highway between each major intersection to the values given in Exhibit 23. If all of the section volumes fall in the level of service E range or better, there will not be congestion spill over requiring a full facility analysis to better quantify the performance of the facility. One can then use the HCM multilane highway section analysis procedures with defaults for some of the inputs to evaluate the performance of each section. The service volumes in Exhibit 23 can also be used to quickly determine the geographic and temporal extent of the multilane highway that will require analysis. If the counted or forecasted volumes for a section fall below the agency s target LOS standard, then the section can be excluded from a more detailed analysis. Any section that exceeds the capacity values in Exhibit 23 will have queuing that may impact upstream sections and reduce downstream demands. In such a situation a full facility analysis is required to ascertain the performance of the highway. At present the HCM does not provide such an analysis procedure so the analyst would have to resort to microsimulation or some other system analysis approach. The analyst may also use the capacities in Exhibit 23 to compute the peak hour, peak direction demand/capacity ratio for each section under various improvement options. The options can then be quickly ranked according to their forecasted demand/capacity ratios for the critical sections of the highway. Estimating Multilane Highway Service Volumes The approximate maximum average annual daily traffic (AADT) (two-way) that can be accommodated by a multilane highway at a given level of service can be estimated from Exhibit 23. For example, a 4-lane highway (2 lanes each direction) can carry between 49,600 (12,400 x 4 lanes) and 65,600 (16,400 x 4 71

72 lanes) AADT at LOS E, depending on its location (urban or rural) and the terrain type. Higher AADT s can be accommodated at lower K (peak hour proportion) and D (directional proportion) factors. A multilane highway in an urban setting delivers between 85% and 90% of the capacity per lane as an urban freeway. A rural multilane highway delivers 95% to 98% of the capacity per lane as a rural freeway. Exhibit 23: Daily and Peak Hour Service Volume and Capacity Table for Multilane Highway Sections Peak Hour Peak Direction (veh/h/ln) AADT (2way veh/day/2way ln) Type Terrain LOS E LOS E LOS A-C LOS D LOS A-C LOS D (capacity) (capacity) Urban Level ,600 14,800 16,400 Urban Rolling ,700 13,700 15,200 Rural Level ,000 11,800 13,800 Rural Rolling ,100 10,600 12,400 Notes: - Entries are maximum vehicle volumes per lane that can be accommodated at stated level of service (LOS). - AADT = annual average daily traffic. AADT/lane is two-way AADT divided by sum of lanes in both directions. - Urban area assumptions: Free-flow speed = 60 mph, 8% trucks, 0% buses, 0% RVs, 0.93 PHF, driver population factor = 1.00, K factor = 0.10, D factor = Rural area assumptions: Free-flow speed = 60 mph, 12% trucks, 0% buses, 0% RVs, 0.88 PHF, Driver population factor = 1.00, K factor = 0.10; D factor = Values can be adjusted for other assumptions. - K factor is the ratio of weekday peak hour two-way traffic to AADT. - D-factor is the ratio of peak direction traffic to both directions peak hour traffic. - Adapted from Exhibit and Exhibit of HCM When local traffic data suggests that other values for the assumptions than those noted in Exhibit 23 would be more appropriate, the analyst should modify the daily and hourly service volumes using HCM 2010 Equation 14-3 as follows: Equation 29: Modifying the Daily Service Volumes for Alternative Assumptions DSV = DSV 0 f HV f p PHF K D K 0 D 0 f HV,0 f p,0 PHF 0 Where: DSV DSV 0 f HV, f HV,0 f p, f p,0 PHF, PHF 0 K, K 0 D, D 0 = daily service volume (veh/day/ln) = initial daily service volume in Exhibit 23 (veh/day/ln) = desired and initial adjustment factor for presence of heavy vehicles in traffic stream. = desired and initial adjustment factor for unfamiliar driver populations. = desired and initial peak-hour factor. = desired and initial proportion of daily traffic occurring in the peak hour of the day. = desired and initial proportion of traffic in the peak direction during the peak hour. 72

73 The same equation can be used to modify the peak hour peak direction service volumes if the initial peak hour service volumes from Exhibit 23 are used instead of the daily values. Daily service volumes should be rounded to the nearest thousand vehicles, given the many default values used in their computation. Peak hour, peak direction service volumes should be rounded to the nearest ten vehicles. 5. SECTION ANALYSIS USING HCM WITH DEFAULTS Chapter 14 of the 2010 HCM describes the method for evaluating the capacity, speed, density and level of service for multilane highway sections without major intersections (intersections that slow down or stop through traffic on the mainline). Exhibit 24 lists the data needed to evaluate the full range of performance measures for HCM multilane highway section analysis and for the multilane facility analysis method described in this chapter. Exhibit 24: Required Data for Multilane Highway Section Analysis Input Data (units) For Facility Method For HCM Section Default Value Hourly directional volume (veh/h) Must be provided Number of directional lanes Must be provided Terrain type (level, rolling, etc.) Must be provided* Lane width (ft) 12 Total lateral clearance (ft) 12 Access points/mile 8 (rural), 16 (low-density suburban), 25 (high-density suburban) Base free-flow speed (mi/h) 65 Percentage of heavy vehicles (%) 10 (rural), 5 (suburban)** Peak hour factor (decimal) 0.88 (rural), 0.95 (suburban) Driver population factor (decimal) 1.00 Section length (mi) Must be provided Intersection performance data Must be provided *We need to double check the defaults. R. Dowling Notes: See HCM Chapter 14 for definitions of the required input data. Fac = facility method, HCM = HCM section method/software with defaults. *Heavy vehicle impacts on traffic flow on long ( 1 mi) and steep (>4%) grades with relatively few (<5%) trucks can be significantly more severe than the default value for mountainous terrain would indicate. Consideration should be given to developing specific passenger-car-equivalent values for mountainous sections where these conditions are met. **HCM Chapter 26 provides state-specific default values. To evaluate multilane highway sections at a facility level, all of the HCM section-level data listed in Exhibit 24 is required (including section length), plus the intersection-level data for each of the intersection or interchange types found along the multilane facility: 73

74 Section Free-Flow Speeds The base free-flow speed, representing the speed drivers would choose based only on the highway s horizontal and vertical alignment, is a critical input for calculating most multilane highway performance measures. The design speed may be used as the base free-flow speed if it is available. When the multilane highway is divided (with a raised or painted median, or a two-way left-turn lane), has lane widths 12 ft or greater, and total left- and right-side lateral clearance 12 ft or greater, the freeflow speed is equal to the base free-flow speed minus 0.25 mi/h per access point per mile (with a maximum reduction of 10 mi/h). In cases with more constrained roadway geometry, HCM 2010 Chapter 14 can be used to estimate the free-flow speed from the base free-flow speed. The posted speed limit plus an adjustment deemed appropriate by the analyst may be sufficient to estimate the free-flow speed to the nearest 5 mph. Section Capacities The capacity of a multilane highway section depends upon its free-flow speed, the peak hour factor, and the effect of heavy vehicles. The HCM also offers a driver population factor that adjusts capacity downward, but planning analyses often assume that drivers are familiar with the highway and thus no capacity adjustment is made for the driver population. 6. MULTILANE FACILITY ANALYSIS METHOD The multilane highway facility analysis combines the performance estimates produced by the HCM multilane highway section analysis method with the performance results for any controlled intersections on the facility. A controlled intersection is one where the mainline through traffic is required to stop or slow down, such as at a traffic signal, an all-way stop, or a roundabout (see Exhibit 25). A stretch of highway between two controlling intersections may be split into multiple highway sections where there are significant changes in the capacity of the highway (usually caused by changes in the grade, alignment, or number of lanes). Exhibit 25: Controlled Intersections and Sections on Highway Facility Estimation of Facility Free-Flow Speed The facility free-flow speed may be estimated three ways starting with the most accurate field measured approach: The free-flow speed may be directly measured in the field at flow rates below 1,000 vehicles per hour per lane, when measured at least half a mile from a controlled intersection (controlled intersection in this case being defined as any intersection where a signal, a stop sign or a 74

75 roundabout requires mainline traffic to slow down or stop). See the ITE Manual of Transportation Engineering Studies [1] for spot speed measurement techniques. The HCM multilane highway section method also may be used to estimate the free-flow speed. This method is likely to be less accurate than field measurement, but this method requires fewer resources. Finally, the free-flow speed may be estimated as the posted or statutory speed limit plus an adjustment that the analyst judges to be appropriate, often 5 to 7 mi/h. This method is likely to be the least accurate of the three approaches, but it requires the least resources and the accuracy is likely to be sufficient for most planning and preliminary engineering applications. Level of Service The HCM does not define LOS at a facility level for multilane highways. However, the HCM multilane highway section analysis method described in Chapter 14 of the 2010 HCM can be used to estimate the LOS of the sections between controlled intersections and the worst case results reported. The 2010 HCM methods can also be used to estimate the LOS for the controlled intersections on the facility and the worst case results reported. Volume-to-Capacity Ratio The volume/capacity ratios are examined for each section and controlled intersection of the facility. If it is desired to convey a single value to decision makers then the highest v/c ratio should be reported for the facility. Highway Sections The capacities shown in Exhibit 23 may be used to estimate section capacities between controlled intersections. The more detailed HCM section analysis methods with defaults may be used for a more precise estimate. Controlled Intersections The intersection through movement capacities are estimated using the HCM and the procedures described in later in this Guide. Average Travel Speed and Travel Time The total travel time for the facility is computed by summing the section travel times and the intersection delays to mainline through movements. The average speed for the facility is obtained by dividing the length of the facility by the total travel time. Highway Sections Average travel speed is computed by the HCM method for individual sections. The average travel time for a section (excluding any intersection delays) is calculated as the section length divided by the estimated average section speed: TT section = L section S section 3,600 75

76 Equation 30 where TT section = average section travel time (s), L section = section length, including the downstream intersection (mi), S section = average section travel speed (mi/h), and 3,600 = number of seconds in an hour (s/h). The following simplified equation, adapted from HCM Exhibit 14-3, can be used to estimate average section travel speed. The percent base capacity in the equation is used to convert capacities from vehicles per hour per lane to passenger car equivalents. S section = FFS section [a ( (1/PBC) (V section/n) 1,400 ) 1.31 ] b Equation 31 where S section = average section travel speed (mi/h), FFS section = section free-flow speed (mi/h), PBC = percent base capacity selected for computing capacity in Error! Reference source not found.(e.g., 90% = 0.90, 80%=0.80) (decimal), V section = vehicle directional demand volume for the section (veh/h), N = number of directional lanes (ln), 1,400 = multilane highway demand volume where speeds start to decline from the free-flow speed (veh/h/ln), and a, b = parameters as given in Exhibit 26. Exhibit 26: Parameters for Multilane Highway Speed Estimation Free-Flow Speed (mi/h) a b Note: Adapted from HCM Exhibit Facilities For facility analyses, the effects of intersection delays at intersections need to be accounted for. The average travel time along a multilane highway facility is estimated by adding intersection delays for through traffic to the estimated section travel times. The average travel speed for through traffic on the facility is then determined by dividing the total travel time into the facility length. TT facility = i TT i + i d i,thru 76

77 Equation 32 S facility = L facility TT facility 3,600 Equation 33 where TT facility = average facility travel time (s), TT i = average section travel time for section i (s), d i,thru = average through-vehicle intersection control delay at the intersection at the downstream end of section i (s), S facility = average through-vehicle facility travel speed (mi/h), L facility = facility length (mi), and 3,600 = number of seconds in an hour (s/h). Vehicle Hours of Delay Vehicle hours of delay are calculated by comparing the travel time at an analyst-defined target travel speed to the average travel time, and multiplying by the number of through vehicles. The HCM defines the target travel speed as the free-flow speed. However, some agencies use the speed limit as the basis for calculating delay, while others choose a threshold or policy speed that the agency considers to be its minimum desirable operating speed. TT target,section = L section S target,section 3,600 Equation 34 VHD section = (TT section+d thru TT target,section ) V section,thru 3,600 0 Equation 35 VHD facility = i VHD i Equation 36 where TT target, section = target travel time for a section (s), L section = section length, including the downstream intersection (mi), S target,section = target travel speed for the section (mi/h), 3,600 = number of seconds in an hour (s/h), VHD section = vehicle hours of delay to through vehicles in a section (veh-h), TT section = average section travel time (s), 77

78 d thru = average through-vehicle intersection control delay at the intersection at the downstream end of the section (s), V section = vehicle directional demand volume for the section (veh), VHD facility = vehicle hours of delay to through vehicles on the facility (veh-h), and VHD i = vehicle hours of delay to through vehicles in section i (veh-h), Person Hours of Delay Person hours of delay for a section or facility is the corresponding vehicle hours of delay, multiplied by an assumed average vehicle occupancy. Density Section density is computed according to the following equation, adapted from HCM Equation 14-5: D section = (V section/n) S section Equation 37 where D section = section density (pc/mi/ln), V section = vehicle directional demand volume for the section (veh), N = number of directional lanes (ln), S section = average section travel speed (mi/h). Queuing A section is considered 100% in queue if its density exceeds the values shown in Exhibit 27. Exhibit 27: Queue Density Thresholds for Multi-Lane Highways Free-Flow Speed (mi/h) Queue Density Threshold (pc/mi/ln) Note: Adapted from HCM Exhibit Queues are meaningful on multi-lane highways only at the specific bottlenecks causing the queues. Thus queues are estimated and reported by bottleneck (for example, using the appropriate intersection queuing estimation method). Note that the HCM does not provide methods for evaluating nonintersection bottlenecks that may occur on multilane highways where large mid-section demand surges or significant changes in geometry (e.g., lane drops, grade changes) might create a bottleneck. 78

79 7. RELIABILITY (NO METHOD AVAILABLE) There is no method in the HCM or in the literature for estimating the reliability of rural or urban multilane highways. 8. MULTIMODAL LOS The HCM provides a bicycle LOS measure for multilane highways. For details, see the pedestrian and bicycle methods in Chapter 15 Pedestrians, Bicyclists, and Public Transit. The HCM does not provide transit, or pedestrian LOS measures for multilane highways. The truck LOS estimation procedures described in Chapter 16 Truck Level of Service, may be used to estimate truck LOS for multilane highways. 9. EXAMPLE (NONE PROVIDED) Resources were insufficient for preparation of an example problem in this edition of the Guide. 10. REFERENCE 1. Manual of Transportation Engineering Studies, 2 nd edition, Institute of Transportation Engineers, Washington, DC,

80 CHAPTER 10 TWO LANE HIGHWAYS 1. INTRODUCTION Two-lane highways have one lane for the use of traffic in each direction. The principal characteristic that separates the traffic performance of two-lane highways from other uninterruptedflow facilities is that passing maneuvers may be allowed to take place in the opposing lane of traffic. Passing maneuvers are limited by the availability of gaps in the opposing traffic stream and by the availability of sufficient sight distance for a driver to discern the approach of an opposing vehicle safely. As demand flows and geometric restrictions increase, opportunities to pass decrease. This creates platoons within the traffic stream, with trailing vehicles subject to additional delay because of the inability to pass the lead vehicles. Because passing capacity decreases as passing demand increases, two-lane highways exhibit a unique characteristic: operating quality often decreases precipitously as demand flow increases, and operations can become unacceptable at relatively low volume-to-capacity ratios. For this reason, few two-lane highways ever operate at flow rates approaching capacity; in most cases, poor operating quality has led to improvements or reconstruction long before capacity demand is reached. Two lane highways have no access control or partial control of access. Traffic signals, all-way stops, or roundabouts may be found along two lane highways, but must be spaced at least 2 miles apart if the roadway is to be considered a two lane highway for the purposes of the analysis methods presented in this chapter. 2. APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Development of a highway corridor improvement plan. Assessment of the impacts on facility performance of changing or adding intersection controls. Feasibility studies of: o Truck climbing lanes o Passing lanes Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW The HCM provides a method for estimating the performance of two-lane highway sections in between intersections. It does not provide a method or level of service measures for evaluating two-lane 80

81 highway facilities, combining the operations of sections with signalized, stop, or roundabout controlled intersections. This chapter presents: 1. A high level screening/scoping method that can be used to focus the analysis on only those locations and time periods requiring investigation (see Exhibit 22). 2. The HCM mid-level method for evaluating two-lane highway section performance using defaults. 3. A mid-level procedure for combining intersection and section performance into estimating twolane highway facility performance. Exhibit 28: Analysis Options for Two-lane Highways 4. SCOPING AND SCREENING Whether or not a more detailed two lane highway analysis is needed can be determined by comparing the counted or forecasted peak hour or daily traffic volumes for the sections of the highway between each major intersection to the values given in Exhibit 29. If all of the section volumes fall in the level of service E range or better, there will not be congestion spill over requiring a full facility analysis to better quantify the performance of the facility. One can then use the HCM multilane highway section analysis procedures with defaults for some of the inputs to evaluate the performance of each section. The service volumes in Exhibit 29 can also be used to quickly determine the geographic and temporal extent of the multilane highway that will require analysis. If the counted or forecasted volumes for a section fall below the agency s target LOS standard, then the section can be excluded from a more detailed analysis. Any section that exceeds the capacity values in Exhibit 29 will have queuing that may impact upstream sections and reduce downstream demands. In such a situation a full facility analysis is required to 81

82 ascertain the performance of the highway. At present the HCM does not provide such an analysis procedure so the analyst would have to resort to microsimulation or some other system analysis approach. The analyst may also use the capacities in Exhibit 29 to compute the peak hour, peak direction demand/capacity ratio for each section under various improvement options. The options can then be quickly ranked according to their forecasted demand/capacity ratios for the critical sections of the highway. Estimating Two Lane Highway Service Volumes The approximate maximum average annual daily traffic (AADT) (two-way) that can be accommodated by a two lane highway at a given level of service can be estimated from Exhibit 29. For example, a 2 lane highway can carry between 24,100 and 24,900 AADT at LOS E, depending on its class and the terrain type. Higher AADT s can be accommodated at lower K (peak hour proportion) and D (directional proportion) factors. Exhibit 29: Daily and Peak Hour Service Volume and Capacity Table for Two Lane Highway Sections Peak Hour Peak Direction (veh/h/ln) AADT (2way veh/day) Type Terrain LOS E LOS E LOS A-C LOS D LOS A-C LOS D (capacity) (capacity) Class I Level ,300 12,500 24,900 Class I Rolling ,600 11,500 24,100 Class II Rolling ,100 13,100 24,900 Notes: - Entries are maximum vehicle volumes per lane that can be accommodated at stated level of service (LOS). - AADT = annual average daily traffic. AADT/lane is two-way AADT divided by sum of lanes in both directions. - Assumed values for Class I level: BFFS = 65 mi/h, 20% no-passing zones. - Assumed values for Class I rolling: BFFS = 60 mi/h, 40% no-passing zones. - Assumed values for Class II rolling: BFFS = 50 mi/h, 60% no-passing zones. - Values can be adjusted for other assumptions. - K factor assumed to be 0.10 for all classes. K factor is the ratio of weekday peak hour two-way traffic to AADT. - D-factor assumed to be D factor is the ratio of peak direction traffic to both directions peak hour traffic. - Adapted from Exhibit of HCM When local traffic data suggests that other values for the assumptions than those noted in Exhibit 29 would be more appropriate, the analyst should modify the daily and hourly service volumes using HCM 2010 Equations and 15-33, adapted as follows: 82

83 Equation 38: Modifying the Daily Service Volumes for Alternative Assumptions DSV = DSV 0 f HV f p PHF K D Where: DSV DSV 0 f HV, f HV,0 f p, f p,0 PHF, PHF 0 K, K 0 D, D 0 K 0 D 0 f HV,0 f p,0 PHF 0 = daily service volume (veh/day/ln) = initial daily service volume in Exhibit 23 (veh/day/ln) = desired and initial adjustment factor for presence of heavy vehicles in traffic stream. = desired and initial adjustment factor for unfamiliar driver populations. = desired and initial peak-hour factor. = desired and initial proportion of daily traffic occurring in the peak hour of the day. = desired and initial proportion of traffic in the peak direction during the peak hour. The same equation can be used to modify the peak hour peak direction service volumes if the initial peak hour service volumes from Exhibit 29 are used instead of the daily values. Daily service volumes should be rounded to the nearest thousand vehicles, given the many default values used in their computation. Peak hour, peak direction service volumes should be rounded to the nearest ten vehicles. 5. SECTION ANALYSIS USING HCM WITH DEFAULTS Chapter 15 of the 2010 HCM describes the method for evaluating the capacity, speed, density and level of service for two lane highway sections without major intersections (intersections that slow down or stop through traffic on the mainline). Exhibit 30 lists the data needed to evaluate the full range of performance measures for HCM two lane highway section analyses and for the two lane facility analysis method described in this chapter. To evaluate two lane highway sections at a facility level, all of the HCM section-level data listed in Exhibit 30 is required (including section length), plus the intersection-data for the two lane facility: The HCM section method starts by estimating the free-flow speed based on the geometry of the section and the characteristics of the traffic demands (percent heavy vehicles). The average travel speed is then estimated, followed by the percent time spent following. Finally, the level of service and capacity are estimated. 83

84 Exhibit 30: Required Data for Two lane Highway Section Analysis Input Data (units) For Facility Method For HCM Section Default Value Hourly directional volume (veh/h) Must be provided Locations and lengths of passing lanes Must be provided Terrain type (level, rolling, etc.) Must be provided* Lane width (ft) 12 Total lateral clearance (ft) 12 Base free-flow speed (mi/h) 65 Percentage of heavy vehicles (%) 10 (rural), 5 (suburban)** Peak hour factor (decimal) 0.88 (rural), 0.95 (suburban) Section length (mi) Must be provided Intersection performance data Must be provided *We need to double check the defaults. R. Dowling Notes: See HCM Chapter 15 for definitions of the required input data. Facility = facility method, HCM = HCM section method/software with defaults. *Heavy vehicle impacts on traffic flow on long ( 1 mi) and steep (>4%) grades with relatively few (<5%) trucks can be significantly more severe than the default value for mountainous terrain would indicate. Consideration should be given to developing specific passenger-car-equivalent values for mountainous sections where these conditions are met. **HCM Chapter 26 provides state-specific default values. Section Level of Service Section-level LOS is an output of the HCM method; step-by-step calculation details are provided in HCM Chapter 15. Exhibit 31 presents the auto LOS criteria for two-lane highway sections. The HCM does not define LOS at a facility level for two lane highways. Two lane highway sections are divided into three classes for the purpose of LOS analysis: Class I two-lane highways are highways where motorists expect to travel at relatively high speeds. Two-lane highways that are major intercity routes, primary connectors of major traffic generators, daily commuter routes, or major links in state or national highway networks are generally assigned to Class I. These facilities serve mostly long-distance trips or provide the connections between facilities that serve long-distance trips. Class II two-lane highways are highways where motorists do not necessarily expect to travel at high speeds. Two-lane highways functioning as access routes to Class I facilities, serving as scenic or recreational routes (and not as primary arterials), or passing through rugged terrain (where high-speed operation would be impossible) are assigned to Class II. Class II facilities most often serve relatively short trips, the beginning or ending portions of longer trips, or trips for which sightseeing plays a significant role. Class III two-lane highways are highways serving moderately developed areas. They may be portions of a Class I or Class II highway that pass through small towns or developed recreational areas. On such sections, local traffic often mixes with through traffic, and the density of 84

85 unsignalized roadside access points is noticeably higher than in a purely rural area. Class III highways may also be longer sections passing through more spread-out recreational areas, also with increased roadside densities. Such sections are often accompanied by reduced speed limits that reflect the higher activity level. Exhibit 31 shows the level of service criteria for each highway class. Exhibit 31: Auto Level of Service Criteria for Two Lane Highway Sections Class I Highways Class II Highways Class III Highways LOS ATS (mi/h) PTSF (%) PTSF (%) PFFS (%) A > >91.7 B >50 55 >35 50 >40 55 > C >45 50 >50 65 >55 70 > D >40 45 >65 80 >70 85 > Notes: E 40 >80 > ATS = average travel speed (excluding intersection delays) (mi/h) - PTSF = percent time spent following (%) - PFFS = percent of free-flow speed away from signalized or other controlling intersections (e.g. roundabouts and all-way stops) (%). - Adapted from exhibit 15-3, 2010 HCM. 6. TWO LANE FACILITY ANALYSIS METHOD The two lane highway facility analysis combines the performance estimates produced by the HCM two lane highway section analysis method with the performance results for any controlled intersections on the facility. A controlled intersection is one where the mainline through traffic is required to stop or slow down, such as at a traffic signal, an all-way stop, or a roundabout (see Exhibit 32). A stretch of highway between two controlling intersections may be split into multiple highway sections where there are significant changes in the capacity of the highway (usually caused by changes in the grade, alignment, or number of lanes). Exhibit 32: Controlled Intersections and Sections on Highway Facility 85

86 Estimation of Facility Free-Flow Speed The facility free-flow speed may be estimated three ways starting with the most accurate field measured approach: The free-flow speed may be estimated by adjusting measurements in the field following the guidance provided in Chapter 15 of the 2010 HCM. (It is difficult to find low enough volumes in the field for direct measurement, so the HCM adjustments are required). The Chapter 15 HCM two-lane highway section method also may be used to estimate the freeflow speed. This method is likely to be less accurate than field measurement, but this method requires fewer resources. Finally, the free-flow speed may be estimated as the posted or statutory speed limit plus an adjustment that the analyst judges to be appropriate, often 5 to 7 mi/h. This method is likely to be the least accurate of the three approaches, but it requires the least resources and the accuracy is likely to be sufficient for most planning and preliminary engineering applications. Level of Service The HCM does not define LOS at a facility level for two-lane highways. However, the HCM two-lane highway section analysis method described in Chapter 15 of the 2010 HCM can be used to estimate the LOS of the sections between controlled intersections and the worst case results reported. The 2010 HCM methods can also be used to estimate the LOS for the controlled intersections on the facility and the worst case results reported. Volume-to-Capacity Ratio The volume/capacity ratios are examined for each section and controlled intersection of the facility. If it is desired to convey a single value to decision makers then the highest v/c ratio should be reported for the facility. Highway Sections The capacities shown in Exhibit 29 may be used to estimate section capacities between controlled intersections. The more detailed HCM section analysis methods with defaults may be used for a more precise estimate. Controlled Intersections The intersection through movement capacities are estimated using the HCM and the procedures described in later in this Guide. Average Travel Speed and Average Travel Time The total travel time for the facility is computed by summing the section travel times and the intersection delays to mainline through movements. The average speed for the facility is obtained by dividing the length of the facility by the total travel time. 86

87 Highway Sections Average travel speed is computed by the HCM method for individual sections. The average travel time for a section (excluding any intersection delays) is calculated as the section length divided by the section speed: where TT section = L section S section 3, 600 TT section = average section travel time (s), L section = section length, including the downstream intersection (mi), S section = average section travel speed (mi/h), and 3,600 = number of seconds in an hour (s/h). Equation 39 The estimated free-flow speed should include the effects of narrow lane widths right side lateral clearance, and access point density (See Chapter 15, HCM 2010 for details). The percent base capacity in the equation is used to convert capacities from vehicles per hour per lane to passenger car equivalents. S = FFS ( v d+v o PBC ) FNP Where: S = average section speed (mi/h) FFS = free-flow speed (mi/h) V d = vehicles per hour per lane in subject direction (veh/h) V o = flow rate in opposite direction (veh/h) PBC = percent base capacity selected for computing capacity (90%, 80%, etc.) FNP = adjustment factor for percent no-passing zones on section, as given in Exhibit 33. Exhibit 33: No-Passing Adjustment for Two-Lane Highway Speed Estimation Equation veh/h < Opposing Flow rate < 500 veh/h All Other Free-Flow Speed (mi/h) 0% No 100% No Passing Opposing Flow 50% No Passing Passing Rates Notes: Entries are speed reductions in mi/h. Adapted from Exhibit of 2010 HCM 87

88 To estimate the percent time spent following, the procedures described in Chapter 15, HCM 2010 should be used. Facilities For facility analyses, the effects of intersection delays at intersections need to be accounted for. The average travel time along a two lane highway facility is estimated by adding intersection delays for through traffic to the estimated section travel times. The average travel speed for through traffic on the facility is then determined by dividing the total travel time into the facility length. TT facility = i TT i + i d i,thru S facility = L facility TT facility 3,600 Equation 41 Equation 42 where TT facility = average facility travel time (s), TT i = average section travel time for section i (s), d i,thru = average through-vehicle intersection control delay at the intersection at the downstream end of section i (s), S facility = average through-vehicle facility travel speed (mi/h), L facility = facility length (mi), and 3,600 = number of seconds in an hour (s/h). Vehicle Hours of Delay Vehicle hours of delay are calculated by comparing the travel time at an analyst-defined target travel speed to the average travel time, and two plying by the number of through vehicles. The HCM defines the target travel speed as the free-flow speed. However, some agencies use the speed limit as the basis for calculating delay, while others choose a threshold or policy speed that the agency considers to be its minimum desirable operating speed. TT target,section = L section S target,section 3,600 Equation 43 VHD section = (TT section+d thru TT target,section ) V section,thru 3,600 0 Equation 44 VHD facility = i VHD i 88

89 where TT target, section = target travel time for a section (s), L section = section length, including the downstream intersection (mi), S target,section = target travel speed for the section (mi/h), 3,600 = number of seconds in an hour (s/h), VHD section = vehicle hours of delay to through vehicles in a section (veh-h), TT section = average section travel time (s), d thru = average through-vehicle intersection control delay at the intersection at the downstream end of the section (s), V section = vehicle directional demand volume for the section (veh), VHD facility = vehicle hours of delay to through vehicles on the facility (veh-h), and VHD i = vehicle hours of delay to through vehicles in section i (veh-h), Equation 45 Person Hours of Delay Person hours of delay for a section or facility is the corresponding vehicle hours of delay, two plied by an assumed average vehicle occupancy. Density Section density is computed according to the following equation, adapted from HCM Equation 14-5: D section = (V section/n) S section Equation 46 where D section = section density (pc/mi/ln), V section = vehicle directional demand volume for the section (veh), N = number of directional lanes (ln), S section = average section travel speed (mi/h). Queuing Queues are meaningful on two -lane highways only at the specific bottlenecks causing the queues. Thus queues are estimated and reported by bottleneck (for example, using the appropriate intersection queuing estimation method). Note that the HCM does not provide methods for evaluating nonintersection bottlenecks that may occur on two lane highways where large mid-section demand surges or significant changes in geometry (e.g., lane drops, grade changes) might create a bottleneck. 7. RELIABILITY (NO METHOD AVAILABLE) There is no method in the HCM or in the literature for estimating the reliability of rural two lane highways. 89

90 8. MULTIMODAL LOS The HCM provides a bicycle LOS method for two-lane highways. See Chapter 15 Pedestrians, Bicyclists, and Public Transit for more information. The truck LOS method described in Chapter 16 Truck Level of Servicecan be applied to two-lane highways. Transit and pedestrian LOS methods are not available. 9. EXAMPLE (NONE PROVIDED) Resources were insufficient for preparation of an example problem in this edition of the Guide. 10. REFERENCE 90

91 CHAPTER 11 URBAN STREETS 1. INTRODUCTION Any street or roadway with signalized intersections, stop-controlled intersections, or roundabouts that are spaced no farther than 2 mi apart can be evaluated using the HCM methodology for urban streets and the procedures described here in this chapter. The planning methods for urban streets focus on facility level analysis, segment level analysis, and intersection level analysis. Facility level performance is estimated by summing the segment (between intersections) and intersection level performance results. Interchange Ramp Terminals are a special case of signalized intersections at the foot of freeway on and off-ramps. They are dealt with in Chapter 23 of the 2010 HCM. The uneven nature of lane demands and the tight spacing between signals within a freeway interchange results in conditions than are not typical of an urban street. An urban street segment is a segment of roadway bounded by intersections at either end. An urban street facility is a set of contiguous urban street segments. The control delay at the downstream intersection defining a segment is included in the segment travel time. Exhibit 34 shows the relationship between an urban street facility, an urban street segment, and an intersection as well as the segment travel time and intersections control delay. 2. APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Development of an urban street corridor improvement plan. Feasibility studies of: o Road diets o Complete streets o Capacity improvements o Signal timing improvements o Transit priority timing Land development traffic impact studies. 91

92 Exhibit 34: Relationships between Urban Street Facility, Urban Street Segment, and Intersections This diagram shows only one direction of a typical bi-directional urban street analysis. 3. ANALYSIS METHODS OVERVIEW Urban street performance can be directly measured in the field or it can be estimated in great detail using microsimulation. However the resource requirements of both of these methods render them generally impractical for most planning and preliminary engineering applications. The HCM provides a less resource intensive approach to estimating urban street performance, however; it also is generally impractical to use the HCM with 100% field measured inputs for many planning and preliminary engineering analyses. This chapter presents two mid-level methods for evaluating urban street performance plus a high level screening/scoping method that can be used to focus the analysis on only those locations and time periods requiring a deeper investigation (see Exhibit 35). 92

93 Exhibit 35: Analysis Options for Urban Streets The HCM segment, intersection, and facility analysis methods (covered in Chapters 16 to 23 of the HCM 2010) provide a good basis for estimating urban street performance under many conditions. The methods are complex, so specialized software is required to implement these methods. A simplified HCM facility analysis method is consequently presented in this chapter to reduce the number of computations and enable programming of the method in a static spreadsheet, without requiring writing any Visual Basic code to implement it. Because all of these methods still require a fair amount of data and computations, this chapter also provides a high level service volume and v/c ratio screening method for quickly identifying which portions of the street will require more detailed analysis (to properly account for the spillover effects of congestion), and to quickly compare improvement alternatives according to the capacity they provide. 4. SCOPING AND SCREENING Whether or not a more detailed urban street facility analysis is needed can be determined by comparing the counted or forecasted peak hour or daily traffic volumes for the segments of the urban street between each controlled intersection to the values given in Exhibit 36. If all of the segment volumes fall in the level of service E range or better, there will not be congestion spillover requiring a full facility analysis to better quantify the performance of the facility. One can then use the HCM intersection and segment analysis procedures with defaults for some of the inputs to evaluate the performance of each segment and intersection. The service volumes in Exhibit 36 can also be used to quickly determine the geographic and temporal extent of the urban street facility that will require analysis. If the counted or forecasted volumes for a segment fall below the agency s target LOS standard, then the segment and its associated downstream intersection can be excluded from a more detailed analysis. 93

94 Facility Service Volume Check The approximate maximum average annual daily traffic (AADT) (two-way) that can be accommodated by an urban street at a given level of service can be estimated from Exhibit 36. For example, a 6-lane urban street (3 lanes each direction) can carry between 40,000 and 50,000 AADT at LOS E, depending on the posted speed limit, the peak hour factor (K-Factor) and the directional factor (D-Factor). Exhibit 36: Service Volume Table for Urban Streets (AADT and Peak Hour) AADT/Lane (counting lanes and volumes in both directions) Speed Limit Free-Flow Signal (mi/h) Speed (mi/h) Spacing (ft) LOS C/D LOS D/E LOS E/F ,800 5, ,320 3,800 6,400 6, , ,700 6, ,640 6,700 7,000 7, ,640 6,000 6,800 7, ,640 6,100 6,700 7, ,280 7,000 7,500 8,400 Peak Hour, Peak Direction (veh/h/ln) (counting lanes and volumes in peak direction) Speed Limit Free-Flow Signal (mi/h) Speed (mi/h) Spacing (ft) LOS C/D LOS D/E LOS E/F , , , , , , Notes: General assumptions include no roundabouts or all-way STOP-controlled intersections along the facility; coordinated, semi-actuated traffic signals; arrival type 4 for peak direction; 100-s cycle time for 25 mph street, 100 second cycle time for 35 mph street with 1,320 ft signal spacing; 150 second cycle time for all others; protected left-turn phases; 0.45 weighted average g/c ratio; exclusive left-turn lanes with adequate queue storage provided at traffic signals; no exclusive right-turn lanes provided; no restrictive median; 10% of traffic turns left and 10% turns right at each traffic signal; peak hour factor = 0.92, and effective saturation flow rate = 1,700 veh/h/ln (after adjustments for turns, heavy vehicles, and other effects). AADT computed assumed K = 0.10 and D = for other values of K and D, multiply AADTs by these factor values (0.10 and 0.60) and divide by desired K and D factors. 94

95 Intersection Volume/Capacity Ratio Checks The problem with screening at the facility level is that it is possible at the facility LOS E/F range to have already exceeded the capacity of one or more intersections on the arterial. This is especially likely when the signals are widely spaced (more than one quarter mile apart) (see Exhibit 37). Thus, an intersection v/c check is recommended to supplement the overall facility service volume screening. The intersection volume/capacity ratios are computed and screened using the methods described in the intersection chapters of this Guide. The v/c ratios may be used for study scoping purposes to identify those intersections requiring more detailed analysis. They may also be used to quickly screen capacity related improvement alternatives. Any segment that exceeds the capacity of the downstream intersection will have queuing that may impact upstream segments and reduce downstream demands (see Exhibit 37). In such a situation a full urban street facility analysis using a method capable of accurately identifying queue spill backs is required to ascertain the performance of the urban street. The facility analysis can be performed using the HCM method with defaults, described later in this chapter. In cases of severe congestion, a microsimulation analysis may be required to accurately assess queue spillback effects. Exhibit 37: Signal Approach Operating Characteristics for Given Arterial LOS Thresholds Signal Approach V/C Speed Limit Free-Flow Signal (mi/h) Speed (mi/h) Spacing (ft) LOS C/D LOS D/E LOS E/F , , , , , , Signal Approach Average Queue (ft) Speed Limit Free-Flow Signal (mi/h) Speed (mi/h) Spacing (ft) LOS C/D LOS D/E LOS E/F , , , , , , , ,129 1,747 95

96 The analyst may also use the intersection demand/capacity ratios for each segment to quickly screen various capacity improvement options. Exhibit 38 shows the planning capacities per through lane that may be used to screen for signalized intersection capacity problems. The options can then be quickly ranked according to their forecasted demand/capacity ratios for the critical segments of the urban street. Exhibit 38: Signal Approach Through Capacities Saturation Flow Rate (vphg/ln) Through Movement Effective g/c Notes: Entries are through vehicles per hour per through lane. - If exclusive turns lanes are present on the signal approach, then the total approach volumes used to screen for capacity problems should be reduced by the number of turning vehicles. A default value of 20% turns (10% lefts, 10% rights) may be used where both exclusive left and right turn lanes are present. - Saturation flow rates are effective rates after adjustment for heavy vehicles, turns, peak hour factor, and other factors affecting saturation flow. - Effective g/c s are after adjustment for start-up and clearance loss times and the proportion of the cycle consumed by turning movement phases and cross-street phases. 96

97 5. EMPLOYING THE HCM METHOD WITH DEFAULTS The HCM facility analysis method is described in Chapter 16 of the 2010 HCM. Exhibit 39 lists the data needed to evaluate the full range of performance measures for planning-level urban street analysis. Individual performance measures may require only a subset of these inputs. Exhibit 39: Required Data for Urban Street Analysis Required to Estimate Input Data (units) MM Comments/Defaults FFS Cap Spd LOS Que Rel LOS Posted Speed Limit (mi/h) required Median type required Presence of curb required Access points per mile required Number of Through lanes required Segment length (mi) required Segment demands required Segment lane geometry Intersection control data See intersection chapter Intersection demands See intersection chapter Intersection geometry See intersection chapter Analysis Period Length (h) 0.25 h Seasonal demand variation Defaults in HCM Incident frequency/duration Defaults in HCM Local weather history Defaults in HCM Workzone probability Defaults in HCM *We need to double check the defaults. R. Dowling Notes: See appropriate sections in text for definitions of the required input data. - FFS = free-flow speed (default = speed limit plus 5 mi/h) - Cap = Capacity (veh/hr/ln) - Spd = Speed (mi/h) - LOS = auto level of service (If service volume table used, only AADT, K, D, and number of lanes required) - MMLOS = multimodal LOS (transit, bike, ped) - Que = Queue (veh) - Rel = Travel Time Reliability - Data required for intersection analysis is not shown here. See appropriate intersection chapter. The estimation of free-flow speeds using the Chapter 17 HCM 2010 method requires information on the posted speed limit, median type, presence of a curb, the number access points per mile, the number of through lanes, and signal spacing. 97

98 Urban street capacity, which is determined by the through capacities of the controlled intersections, requires intersection control data, intersection demands, intersection lane geometry, and the analysis period length. Speed, level of service, and multimodal LOS require the intersection capacities and free-flow speed plus additional data on segment lengths, demands, and lanes. Queues are estimated based on the intersection control, demand, and geometric data. Reliability analysis requires all the data required to estimate speeds plus additional information on the variability of demands, incident frequencies and duration, weather, and workzones. 98

99 6. SIMPLIFIED HCM FACILITY ANALYSIS METHOD This simplified urban street facility analysis method assumes that the segments between intersections have no access points between the intersection boundaries and that there are no turning movements at the intersection. All intersections are assumed to be signalized. The method does not consider the effects of a median. A flow diagram showing the analysis steps for the method is provided in in Exhibit 40. Exhibit 40: Simplified Urban Street Analysis Method Steps Input Requirements The method requires data for four input parameters: 1. The through movement volume along the segment, v m (veh/hr), 2. The number of through lanes on the segment, N TH, 3. The length of the segment, L (ft), and 4. The posted speed limit along the segment, S pl (mi/hr). Default values are assumed for five other input parameters: 99

100 Through movement saturation flow rate, s = 1900 veh/hr/ln, Effective green ratio, g/c = 0.45, Cycle length, C = 120 sec, Quality of progression along the segment = average, and Duration of analysis period, T = 0.25 hr. As a default, the cycle length is assumed to be 120 sec and the effective green ratio is assumed to be This value assumes that the green time is evenly divided between the north-south and east-west approaches to the intersection and that lost time accounts for ten percent of the cycle length. The analyst can override these defaults if data for cycle length or effective green ratio are available. The quality of progression is assumed to be average (random arrivals), but the analyst can select either good (if there is some degree of coordination between the two signalized intersections, or poor (if there is poor coordination between the intersections). Step 1: Calculate running time. The running time t R is calculated using Equation 47. Equation 47 where t R = 5280S pl + U ADJ 3600L S pl = posted speed limit (mi/hr), U ADJ = user adjustment to account for differences between the posted speed limit and the average travel speed of drivers on the facility; and L = length of the segment, (ft). Step 2: Calculate the capacity c (veh/hr) of the downstream intersection. The capacity of the downstream intersection is calculated using Equation 48. where c = v m N TH s v m = through movement volume (veh/hr), N TH = number of through lanes, and s = through movement saturation flow rate (veh/hr/ln). Equation

101 Step 3: Calculate the volume-to-capacity ratio. The volume-to-capacity ratio X is calculated using Equation 49. Equation 49 X = v m c where v m = through movement volume along the segment (veh/hr), and c = capacity of the downstream intersection (veh/hr). Step 4: Calculate the control delay. The control delay d (sec/veh) is determined either from the signalized intersection planning method (see section 2) or calculated as described below. The uniform delay term d 1 (sec/veh) is calculated using Equation 50. where C = cycle length (sec), g/c = effective green ratio, and X = volume-to-capacity ratio. d 1 = 0.5C(1 g/c) 2 1 [min(1, X) (g/c)] Equation 50 The incremental delay term d 2 (sec/veh) is calculated using Equation 51. Equation 51 d 2 = 225 [(X 1) + (X 1) X cn ] where X = volume-to-capacity ratio, c = capacity (veh/hr), and N = number of lanes. 101

102 The control delay is calculated using Equation 52. Equation 52 d = d 1 PF + d 2 where d 1 = uniform delay term (sec/veh), PF = progression adjustment factor, and d 2 = incremental delay term (sec/veh). The progression factor is a function of the quality of signal progression as given in Exhibit 41. Exhibit 41. Progression Factor Quality of progression Good (some degree of coordination between the two signalized intersections Average (random arrivals) Poor (poor coordination between the intersections) Progression factor (PF) Step 5: Calculate the travel speed and determine level of service. The travel time on the segment T T (sec) is calculated using Equation 53. Equation 53 T T = t R + d where t R = running time (sec), and d = control delay (sec/veh). The travel speed on the segment S T,seg (mi/hr) is calculated using Equation 54. Equation

103 S T,seg = 3600L 5280T T where L = segment length (ft), and T T = travel time on the segment (sec). A spreadsheet computational engine has been developed for use in computing each of the data elements. Worksheets for completing the calculations are provided below. Exhibit 42: Simplified Urban Street Method Worksheets Simplified Urban Street Method, Input Data Worksheet Input Data Direction 1 (EB/NB) Direction 2 (WB/SB) Through movement volume, v m (veh/h) Number of through lanes, N TH Segment length, L (ft) Posted speed limit, S pl (mi/h) Through movement saturation flow rate, s (veh/h/ln) Effective green ratio, g/c Cycle length, C (s) Quality of progression (Good, Average, Poor) Average Average Analysis period, T (h) Simplified Urban Street Method, Calculation Worksheet Step 1. Running Time Direction 1 (EB/NB) Direction 2 (WB/SB) Running time: t R = 5280S pl 3600L Step 2. Capacity Direction 1 (EB/NB) Direction 2 (WB/SB) Capacity: c = v m N TH s Step 3. VolumH-to-Capacity Ratio Direction 1 (EB/NB) Direction 2 (WB/SB) VolumH-to-capacity ratio: X = v m c Step 4. Control Delay Direction 1 (EB/NB) Direction 2 (WB/SB) Uniform delay: d 1 = Incremental delay: 0.5C(1 g/c) 2 1 [min(1,x)(g/c)] d 2 = 225 [(X 1) + (X 1) X cn ] Progression factor, PF Control delay: d = d 1 PF + d 2 Step 5. Travel Speed Direction 1 (EB/NB) Direction 2 (WB/SB) Travel time: T T = t R + d Travel speed: S T,seg = 3600L 5280T T 103

104 Cumulative number of vehicles Extension to Oversaturated conditions Cases in which demand exceeds capacity are common in urban street networks, particularly when considering future planning scenarios. This condition is considered to be sustained when demand exceeds capacity over an entire analysis period, and not just for one or two signal cycles. The condition is illustrated in Exhibit 43, where the arrival volume v 1, during the analysis period t 1, exceeds that capacity c for the downstream intersection approach. During the second analysis period, t 2, the arrival volume v 2 is sufficiently low such that the queue that formed during t 1 clears before the end of t 2. The area between the demand line and the capacity line represents the overflow delay experienced by all vehicles arriving during these two analysis periods. Each of the two analysis periods shown in Exhibit 43 represent a number of signal cycles. v 2 v 1 c t 1 t 2 Time Exhibit 43: Overflow Delay When Demand Exceeds Capacity over the Analysis Period By contrast, the delay resulting from the failure of an individual cycle ( the occasional overflow queue at the end of the green interval ) is accounted for by the d 2 term of the delay equation for signalized intersections and urban street segments. This condition is illustrated in Exhibit 44: Delay Resulting When Demand Is Less than Capacity over the Analysis Period where a queue exists for two cycles, but clears in the third cycle. The non-zero slope of the departure line during the green interval is equal to the saturation flow rate. The slope of the capacity line is the product of the saturation flow rate and the green ratio. The condition shown in the figure is not considered to be sustained oversaturation and is therefore not addressed by the method described in this section. 104

105 Cumulative number of vehicles Time r g r g r g Exhibit 44: Delay Resulting When Demand Is Less than Capacity over the Analysis Period Overview of the Method The urban street segment planning method for oversaturated conditions predicts the overflow delay that results when the demand volume on an urban street segment exceeds its capacity. The method also predicts the volume-to-capacity ratio for the first analysis period. The method considers only the through traffic on the segment. The method considers a queue that may exist at the beginning of the analysis period, the queue that exists at the end of the analysis period, and the time that it takes for this queue to clear during a second analysis period. The framework for determining the effect of oversaturation in the urban street segment is shown in Exhibit 45. Exhibit 45: Urban Street Segment Planning Method, Oversaturated Conditions, Analysis Framework Urban Street Segment: Oversaturated conditions TH volume, v TH lanes, N TH Segment length, L Limitations of the Method The method does not consider mid-section movements, or turning movements or lanes at the downstream intersection. The method does not consider the operational impacts of the queue spillback that result from the oversaturated conditions. The method can be used to analyze oversaturated conditions that result from demand exceeding capacity during several analysis periods. But during the final analysis period, the demand must be such that the queue clears during this period. 105

106 Input Requirements The input requirements for the method include the following nine parameters: The arrival volumes v 1 and v 2 (veh/h) for the through movement at the downstream intersection during analysis period 1 (the period of oversaturation) and analysis period 2 (the period when the queue clears), The duration of each analysis period T (h), The segment length L (ft), The initial queue Q 0 (veh) that exists at the beginning of analysis period 1 for the through movement at the downstream intersection, The number of through lanes in the segment N TH, The saturation flow rate s for the downstream signalized intersection (veh/h/ln), and The cycle length C (s) and effective green ratio g/c at the downstream signalized intersection. Default values are assumed for four of these parameters: T = 0.25 h s = 1900 veh/h/ln C = 120 s g/c = 0.45 Computational Steps The planning method for urban street segments during periods of oversaturation is a simplified version of the operational analysis method for urban street segments for oversaturated conditions described in chapter 30 of the HCM. The method includes nine steps, shown in Exhibit 46 and described below. 106

107 Exhibit 46: Urban Street Segment Planning Method, Oversaturated Conditions Step 1: Calculate Queue Storage Capacity Calculate the queue storage capacity, Q cap (veh) available in the segment. The queue storage capacity is the number of vehicles that can be stored in the segment, assuming an average vehicle length of 25 ft. The queue storage capacity is calculated using Equation 55. where: Q cap = N THL 25 N TH = the number of though lanes in the segment, and L = length of the segment, ft. Equation

108 Step 2: Calculate Available Queue Storage Calculate the available queue storage Q a in the segment during analysis period 1 after accounting for any initial queue Q 0 (veh) that is present at the beginning of the analysis period. The available queue storage is calculated using Equation 56. Equation 56 where Q a = Q cap Q 0 Q cap = the queue storage capacity (veh), and Q 0 = initial queue at the beginning of the analysis period (veh). Step 3: Calculate Capacity of Through Movement Calculate the capacity of the TH movement (c TH ) at the downstream signalized intersection using Equation 57. where: c TH = N TH s ( g C ) s = saturation flow rate for the through movement (veh/h) g = effective green time for the through movement (s), and C = cycle length for the intersection (s). Equation 57 Step 4: Calculate Volume/Capacity Ratio Calculate the volume-to-capacity ratio X for the segment during analysis period 1 using Equation 58. where X = v 1 c TH v 1 = the arrival volume (veh/h) during analysis period 1, and c TH = capacity of the through movement at the downstream intersection (veh/h). Equation

109 Step 5: Calculate Rate of Queue Growth Calculate the rate of queue growth r qg (veh/h) during analysis period 1. If the through movement arrival volume v 1 is less than the capacity, no queue forms and this method is not needed. Equation 59 is used to calculate the rate of queue growth. where r qg = v 1 c TH 0.0 v 1 = the arrival volume (veh/h) during analysis period 1, and c TH = capacity of the through movement at the downstream intersection (veh/h). Equation 59 Step 6: Calculate Queue Length Calculate the length of the queue Q max (veh) at the end of analysis period 1 using Equation 60. Equation 60 where Q max = r qg t 1 r qg = the rate of queue growth (veh/h) during analysis period 1, and t 1 = the duration of analysis period 1 (h). Step 7: Calculate Queue Clearance Rate Calculate the rate of queue clearance r qc (veh) during analysis period 2 using Equation 61. Equation 61 where r qc = c TH v 2 c TH = capacity of the through movement at the downstream intersection (veh/h), and v 2 = the arrival volume (veh/h) during analysis period 2. Step 8: Calculate Queue Clearance Time Calculate the time for the queue to clear after the beginning of analysis period 2. The time for the queue to clear depends on the length of the queue at the end of analysis period 1, the volume during analysis 109

110 period 2, and the capacity of the TH movement for the downstream intersection. If the queue does not clear before the end of analysis period 2, the volumes during subsequent analysis periods must be considered and the queue clearance time calculation must be modified to account for this result. The queue clearance time t c (h) is calculated using Equation 62. where t c = r qgt 1 r qc = Q max c TH v 2 r qg = the rate of queue growth (veh/h) during analysis period 1, t 1 = the duration of analysis period 1 (h), r qc = the rate of queue clearance (veh/h) during analysis period 2, Q max = length of the queue (veh) at the end of analysis period 1, c TH = capacity of the through movement at the downstream intersection (veh/h), and v 2 = the arrival volume (veh/h) during analysis period 2. Equation 62 Step 9: Calculate Oversaturation Delay Calculate the delay resulting from oversaturation d sat (s/veh). Exhibit 47 shows the queue accumulation polygon for oversaturated conditions in which a queue grows during analysis period 1 and clears during analysis period 2. The area of the polygon that is formed by these conditions is the delay resulting from the oversaturated conditions. The average delay per vehicle is calculated using Equation 63. Equation 63 where d sat = 0.5(Q max Q 0 )t t c Q max v 1 t 1 + v 2 t c Q max = length of the queue (veh) at the end of analysis period 1, Q 0 = initial queue at the beginning of the analysis period (veh), t 1 = the duration of analysis period 1 (h), t c = queue clearance time (h), v 1 = the arrival volume (veh/h) during analysis period 1, and v 2 = the arrival volume (veh/h) during analysis period

111 Computational Tools A spreadsheet has been developed for use in calculating each of the data elements. A worksheet for completing the calculations is provided below. Exhibit 47: Queue Accumulation Polygon for Oversaturated Conditions 111

112 Exhibit 48: Urban Street Segment Planning Method, Oversaturated Conditions Worksheet Input Data Urban Street Segment Planning Method, Oversaturated Conditions, Input Data Worksheet Arrival volume, time period 1, v 1 (veh/h) Arrival volume, time period 2, v 2 (veh/h) Duration of each analysis period T (h) Segment length, L (ft) The initial queue Q 0 (veh) Number of through lanes, N TH Through movement saturation flow rate, s (veh/h/ln) Effective green ratio, g/c Cycle length, C (s) Urban Street Segment Planning Method, Oversaturated Conditions, Calculation Worksheet Step 1. Queue Storage Capacity (veh) Q cap = N THL 25 Step 2. Available Queue Storage (veh) Q a = Q cap Q 0 Step 3. Capacity of Through Movement (veh/h) c TH = N TH s ( g C ) Step 4. VolumH-to-Capacity Ratio X = v 1 c TH Step 5. Rate of Queue Growth (veh/h) r qg = v 1 c TH 0.0 Step 6. Length of Queue (veh) Q max = r qg t 1 Step 7. Rate of Queue Clearance (veh/h) r qc = c TH v 2 Step 8. Time of Queue Clearance (h) t c = r qgt 1 r qc = Q max c TH v 2 112

113 7. RELIABILITY ANALYSIS Chapters 36 and 37 of the 2010 Highway Capacity Manual describe a method for estimating urban street reliability that is sensitive to demand variations, weather, incidents, and work zones. The Florida DOT has also developed a method for estimating reliability for urban streets [1]. Both methods are data and computationally intensive requiring custom software to implement. As such, neither method is readily adaptable to a planning and preliminary application that could be programmed in a simple, static spreadsheet. Analysts wishing to perform a reliability analysis of urban streets should consult these sources. 8. MULTIMODAL LOS Truck LOS The 2010 HCM does not provide a truck LOS measure. Chapter 8 Freeway Analyses provides a procedure from NCFRP 41 that can be applied to truck LOS analysis on urban streets. Transit, Bicycle, Pedestrian LOS Procedures for evaluating street transit LOS on an urban street facility are provided in Chapter 15 Pedestrians, Bicyclists, and Public Transit. 9. EXAMPLE Case Study II in Part IV provides an example application of the screening and simplified analysis methods described in this chapter. 10. REFERENCES 1. Elefteriadou, L., Li, Z., Jin, L., FINAL REPORT to THE FLORIDA DEPARTMENT OF TRANSPORTATION SYSTEMS PLANNING OFFICE on Project Modeling, Implementation, and Validation of Arterial Travel Time Reliability, FDOT Contract BDK , University of Florida, Gainesville, FL, November 30,

114 CHAPTER 12 SIGNALIZED INTERSECTIONS 1. INTRODUCTION A signalized intersection is an intersection or midblock crosswalk where some or all conflicting movements are controlled by a traffic signal. The procedures presented here can also be adapted to the analysis of freeway ramp meters and traffic signals used to meter traffic flow into a roundabout. Interchange Ramp Terminals are a special case of signalized intersections at the foot of freeway on and off-ramps. They are dealt with in Chapter 23 of the 2010 HCM. The uneven nature of lane demands and the tight spacing between signals within a freeway interchange results in conditions than are not typical of an urban street. 2. APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Feasibility studies of: o Intersection Improvements o Signal timing improvements Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW Intersection performance can be directly measured in the field or it can be estimated in great detail using microsimulation. However the resource requirements of both of these methods render them generally impractical for most planning and preliminary engineering applications (see Exhibit 49). Chapter 18 of the 2010 HCM provides a much less resource intensive approach to estimating intersection performance, however; it is generally impractical to use the HCM methods with 100% field measured inputs for many planning and preliminary engineering analyses. Employing the HCM method with defaults identified in Chapter 18 of the 2010 HCM reduces the data requirements, but still requires specialized software to implement the complex computations. This chapter presents a mid-level method for evaluating intersections, portions of which can be used to perform a high level screening/scoping to focus the planning and preliminary engineering analysis on only those intersections and time periods requiring investigation. This simplified v/c and LOS method can be easily programmed in a static spreadsheet without requiring knowledge of a programming language such as Visual Basic. 114

115 Exhibit 49: Analysis Options for Signalized Intersections Data Needs Exhibit 17 describes the input data required for conducting a planning analysis for signalized intersections. The analyst is required to specify values for two of the parameters, the volume for each movement and the number of lanes (and the turn designation for each) on each approach. Default values can be assumed for the other seven input parameters, or the analyst can specify the parameter values if they are known. Exhibit 50: Required Data for Signalized Intersection Analysis Required to Estimate Input Data (units) Cap Del LOS MMLOS Que Rel Comments/Defaults Number of turn lanes n/a required Other geometry Defaults provided Signal Timing (cycle, g/c) Defaults provided Peak Hour Factor (decimal) 0.88 (rural), 0.95 (sub.) Percent heavy vehicles (%) 10 (rural), 5 (suburban) Turning demands (veh/h) required Analysis Period Length (h) 0.25 h Notes: See appropriate sections in text for definitions of the required input data. - Cap = Capacity (veh/hr/ln) - Del = Delay (s) - LOS = auto level of service - MMLOS = multimodal LOS (transit, bike, ped) - Que = Queue (veh) - Rel = Travel Time Reliability No Method available for intersections. See Section H. Urban Street. 115

116 - Other geometry includes: lane widths, presence of parking, bus stops, pedestrian crossings, etcetera. - Signal Timing includes: cycle, g/c loss time, progression, phasing, etcetera. - Other demands include: level of pedestrian and parking activity. For the simplified method, parking activity at the intersection is characterized as follows: None (default) Low 5 parking maneuvers per hour Medium 10 parking maneuvers per hour High 15 parking maneuvers per hour Pedestrian activity is characterized as follows: None (default) Low 50 pedestrians per hour Medium 200 pedestrians per hour High 400 pedestrians per hour Very High 800 pedestrians per hour 4. SIMPLIFIED METHOD PART 1 - V/C CALCULATION Whether or not an intersection requires more detailed analysis can be determined quickly by estimating its volume/capacity ratio. Volume/capacity (v/c) ratios can also be used to quickly compare different capacity improvement alternatives and select the more cost-effective alternatives for further analysis. A critical movement analysis is used to predict the critical volume-to-capacity ratio of the intersection and make an assessment of the sufficiency of the intersection to accommodate the forecasted peak hour traffic volumes. Five steps are required to assess the sufficiency of intersection capacity based on the volume/capacity ratio (Exhibit 51). 116

117 Exhibit 51: Intersection Capacity Sufficiency Analysis Steps Step 1: Determine the left-turn phasing. The left turn phasing can be either permitted, protected, protected plus permitted, or split. Permitted phasing enables left turn movements to proceed through the intersection during the same phase as the opposing through movements. Protected phasing assumes that left turn movements are not opposed by any other movements. Protected plus permitted phasing assumes that left turn movements are served during both a protected phase and a permitted phase. Split phasing means that all movements on an approach proceed with no opposing movements. The analyst can select one of these four phasing types if the phasing is known. If it is not known, the computational procedure will determine the left turn phasing. The method will select protected left turn phasing if any of three conditions are met. Otherwise, permitted left turn phasing will be selected. Left turn volume exceeds 200 veh/h, The product of the left turn volume and the opposing through volume exceeds a given threshold (50,000 if there is one opposing through lane, 90,000 if there are two opposing through lanes and 120,000 if there are three or more opposing through lanes), or The number of left turn lanes exceeds one. 117

118 Step 2: Convert turning movements to passenger car equivalents Convert turning movements to passenger car equivalents considering the effect of heavy vehicles, the variation in flow during the hour, the impact of opposing through vehicles on permitted left turning vehicles, the impact of pedestrians on right turning vehicles, lane utilization, and the impact of parking maneuvers on through and right turning vehicles. Step 2a: Heavy Vehicle Adjustment The adjustment for heavy vehicles E HVadj is calculated using Equation 64. where E HVadj = 1 + P HV (E HV 1) P HV = proportion of heavy vehicles in movement, decimal E HV = passenger car equivalent for heavy vehicles in movement (default = 2.0) Equation 64 Step 2b: PHF Adjustment The adjustment for variation in flow during the hour using the peak hour factor PHF is calculated using Equation 65. Equation 65 E PHF = 1 PHF where PHF = peak hour factor (varies between 0.25 and 1.00, default = 0.92) Step 2c: Turn Impedance Adjustment Adjustments for impedances experienced by left and right turning vehicles. Left turning vehicles served by permitted left turn phasing must find acceptable gaps in the opposing through traffic stream to complete their turns. Left turning vehicles served by protected left turn phasing flow more slowly than through vehicles. The values for E LT are given in Exhibit 52. Exhibit 52: Left-Turn Adjustment Factor (E LT ) Opposing Volumes (TH + RT) E LT (veh/h) < >=

119 Right turning vehicles are sometimes impeded by pedestrians. Through vehicles do not experience the impedances that turning vehicles experience, so the flows for these movements are not adjusted. The values for E RT are given in Exhibit 53. Exhibit 53: Right-Turn Adjustment Factor (E RT ) Pedestrian Activity RT Equivalent (E RT ) None or Low 1.2 Medium 1.3 High 1.5 Very High 2.1 Step 2d: Parking adjustment factor The parking adjustment factor E p is a function of the level of parking activity. The values for E p are given in Exhibit 54. Exhibit 54: Parking Adjustment Factor (E p ) Parking Activity Number of Lanes in Lane Group Parking Adjustment Factor, E p No parking lane All 1.00 Adjacent parking Step 2e: Lane utilization factor. The lane utilization factor E LU recognizes the volume imbalance between lanes when there are two or more lanes on an approach. The factor is given in Exhibit 55. Exhibit 55: Lane Utilization Factor (E LU ) Lane Group Movements No. of Lanes in Lane Group Lane Use Equivalency Factor, E LU Through or shared Exclusive LT Exclusive RT Step 2f: Through car equivalent flow rate The through passenger car equivalent flow rate v adj calculated using Equation 66 based on the adjustment factors calculated in steps 2a through 2e. 119

120 Equation 66 v adj = VE HVadj E PHF E LT E RT E p E LU E other where V = turning movement volume (veh/h) E HVadj = equivalency factor to account for heavy vehicles E PHF = equivalency factor to account for peaking characteristics E RT = through-vehicle equivalency factor for right turns E LT = through-vehicle equivalency factor for left turns E p = equivalency factor to account for parking activity E LU = equivalency factor to account for lane utilization E other = equivalency factor to account for other conditions determined by analyst Step 2g. Protected-Permitted Left Turn Analysis Protected-permitted left turn phasing (if present) is analyzed in this sub-step. The signal timing must be known or estimated by the analyst. The left turn equivalent factor E LT calculated in this step would replace the values of E LT from step 2c. The left-turn equivalent to be used to convert passenger cars per hour to through passenger cars per hour is calculated using Equation 67. The left turn equivalent is used to convert the full left turn flow to tcp/h. Note that the effective green time for the first portion of the compound phase includes the yellow interval between the two portions. where E LTC = (E LTPTg LTPT )(E LTPM g LTPM ) g LTPT + g LTPM E LTC = left-turn equivalent for compound LT phasing, E LTPT = left-turn equivalent for the protected portion of the compound LT phase, E LTPM = left-turn equivalent for the permitted portion of the compound LT phase, g LTPT = effective green time for the protected portion of the compound LT phase (s), and g LTPM = effective green time for the permitted portion of the compound LT phase (s). Equation 67 Exhibit 56: Left-Turn Adjustment Factor (E LT ) Opposing Volumes (TH + RT) E LT (veh/h) <

121 >= Step 3: Assign volumes to lane groups. A lane group is a lane or set of lanes designated for separate analysis. All traffic movements for a given approach (i.e., left, through and right) must be assigned to at least one lane group. A lane group can consist of one or more lanes. There are two guidelines for assigning traffic movements to lane groups: 1. When a traffic movement uses only an exclusive lane(s), it is analyzed as an exclusive lane group. 2. When two or more traffic movements share a lane, all lanes which convey those traffic movements are analyzed as a mixed lane group. When a right-turn movement is shared with a through movement, it is considered to be a part of the through movement lane group. When a right-turn movement is shared with a left-turn movement (such as at a T-intersection), it is considered to be a part of the left-turn movement lane group. Lane groups should first be checked to determine if a defacto turn lane exists. A defacto turn lane occurs on approaches with multilane lane groups where either a left-or right-turn movement is shared with a through movement, but that lane is only used by turning vehicles. This occurs in situations where the turning movements are high and/or there are significant impendences for the turning movements. In these situations, defacto turn lanes should be analyzed as exclusive turn lanes and all through movements should be assumed to occur from the through-only lane(s). In cases where there are multiple turn lanes and one lane is shared with a through movement, that combination of lanes should be treated as a single lane group and all the lanes should be associated with the through lane group. For approaches at a T-intersection where there are only left- and right-turn movements and multiple lanes, and one of the lanes is shared, the analyst has the option of coding all lanes as either the right-turn lane group or left-turn lane group. Once lane groups have been defined, the equivalent per lane through movement flow rate v i (pc/h) for lane group i is calculated using Equation 68. where v i = v adj N i Equation 68 v adj = equivalent though movement flow rate (tpc/h or through passenger cars per hour), and N i = number of lanes within lane group i, accounting for defacto lanes. 121

122 Step 4: Calculate critical lane group volumes. Critical lane groups represent the combination of conflicting lane groups from opposing approaches that have the highest total demand. These critical lanes groups thus dictate the amount of green time required during each phase as well as the total cycle length required for the intersection. The movements and phasing for the north-south and east-west approaches are assessed independently. The combination of movements that make up the critical movements are different for protected and permitted left-turn phasing, and for split phasing. Step 4a: Identify critical movements. Protected Left Turn Phasing. When opposing approaches use protected left-turn phasing, the critical lane volumes will be the maximum of the two sums of the left turn lane volume and the opposing through (or shared through) lane volume, or right turn lane volume if that is greater. For the east-west approaches, the critical volume V c,ew is calculated using Equation 69. where V c,ew = Max { v EBLT + Max(v WBTH, v WBTH ) v WBLT + Max(v EBTH, v EBTH ) Equation 69 v EBLT, v WBTH, v WBTH, v WBLT, v EBTH, and v EBTH are the equivalent flow rates (pc/h) for these turning movement. Similarly for the north-south approaches, the critical volume v c,ns is calculated using Equation 70. where V c,ns = Max { v NBLT + Max(v SBTH, v SBTH ) v SBLT + Max(v NBTH, v NBTH ) v NBLT, v SBTH, v SBTH, v SBLT, v NBTH, and v NBTH are the equivalent flow rates (pc/h) for these turning movement. Equation 70 Permitted Left Turn Phasing. When opposing approaches use permitted phasing, the critical lane volume will be highest lane volume of all lane groups for a pair of approaches. For the east-west approaches, the critical volume V c,ew is calculated using Equation 71. V c,ew = Max(v EBLT, v EBTH, v EBTH, v WBLT, v WBTH, v WBTH ) 122 Equation 71

123 where v EBLT, v WBTH, v WBTH, v WBLT, v EBTH, and v EBTH are the equivalent flow rates (pc/h) for these turning movement. Similarly for the north-south approaches the critical volume V c,ns is calculated using Equation 72. where V c,ns = Max(v NBLT, v NBTH, v NBTH, v SBLT, v SBTH, v SBTH ) v NBLT, v SBTH, v SBTH, v SBLT, v NBTH, and v NBTH are the equivalent flow rates (pc/h) for these turning movement. Equation 72 Split Phasing. When opposing approaches use split phasing (where only one approach is served during the phase) the critical lane volume will be highest lane volume of all lane groups for that approach. For the east-west approaches, the critical volume V c,ew will be the sum of: where V c,ew = Max(v EBLT, v EBTH, v EBTH ) + Max(v WBLT, v WBTH, v WBTH ) Equation 73 v EBLT, v WBTH, v WBTH, v WBLT, v EBTH, and v EBTH are the equivalent flow rates (pc/h) for these turning movement. Similarly for the north-south approaches with split phasing, the critical volume V c,ns will be the sum of: where V c,ns = Max(v NBLT, v NBTH, v NBTH ) + Max(v SBLT, v SBTH, v SBTH ) v NBLT, v SBTH, v SBTH, v SBLT, v NBTH, and v NBTH are the equivalent flow rates (pc/h) for these turning movement. Equation

124 Protected-permitted left turn phasing. The signal timing must be known or estimated by the analyst. In order to find the critical lane volumes, the equivalent through-car volume in the left lane during the protected portion of the phase is found (using Equation 75) by splitting the total demand in proportion to the length of the protected green phase to the total compound phase. where g LTPT V LTPT = V LTTOT ( ) g LTPT + g LTPM V LTPT = left-turn demand in protected portion of phase (tcp/h), and V LTTOT = left-turn demand for the total compound LT phase (tcp/h). Equation 75 The critical lane volumes are then found using only the protected portion of the compound phase. The critical lane volume is the highest total of a through-lane volume and its opposing protected left turn volume. The remainder of the methodology does not change. In the delay module, the left-turn demand for the total compound phase (V LTTOT ) is used to find delay. Step 4b: Calculate the sum of the critical lane volumes Calculate the sum of the critical lane volumes Vc using Equation 76. Equation 76 where V c = v c,ew + v c,ns V c,ew = critical volume for the east-west movements (pc/h) V c,ns = critical volume for the north-south movements (pc/h) Step 5: Determine Intersection Sufficiency Step 5a: Calculate the critical volume-to-capacity ratio. Calculate the critical volume-to-capacity ratio X c using Equation 77. where X c = V c c i V ci = sum of the critical lane volumes (pc/h), and Equation

125 c i = intersection capacity (pc/h/ln). Intersection capacity is the maximum per lane flow rate that can be accommodated by the intersection accounting for lost time. A value of 1650 pc/h/ln can be used as a default if local data are not known. This value reflects a saturation flow rate of 1900 pc/h/ln, a lost time of 4 s per critical phase, and a cycle length of 30 s per critical phase. Step 5b: Assess the intersection sufficiency. The final step of the v/c analysis is to assess the sufficiency of the intersection to accommodate a given demand level. Exhibit 57 provides the assessment of intersection sufficiency (under, near, or over) based on the critical volume-to-capacity ratio. Exhibit 57: Intersection Sufficiency X c Description Capacity Assessment <0.85 All demand is able to be accommodated; delays are low to moderate. Under Demand for critical lane groups near capacity and some movements require more Near than one cycle to clear the intersection; all demand is able to be processed at the end of the analysis period; delays are moderate to high. >0.98 Demand for critical movements is just able to be accommodated within a cycle but more oftentimes requires multiple cycles to clear the intersection; delays are high and queues are long. Over 5. SIMPLIFIED DELAY, QUEUE AND LOS CALCULATION Part II of the method includes two steps and produces an estimate of delay. It is based on the results from Part I. The steps are shown in Exhibit 58 and described below. Exhibit 58: Signalized Intersection Planning Method, Part II Step 6. Calculate capacity Step 7. Estimate delay and level of service Step 6: Calculate capacity. Step 6a: Calculate cycle length. The cycle length C (s) is assumed to be 30 seconds per critical phase as shown in the equation below. The analyst can use another value based on local practice or conditions. where C = 30n Equation

126 n = number of critical phases. Step 6b: Calculate total effective green time Calculate the total effective green time g TOT (s) available during the cycle using Equation 79. Equation 79 g TOT = C L where C = cycle length (s), and L = lost time per cycle (s). The total effective green time is then allocated to each critical phase in proportion to the critical lane volume for that movement using Equation 80: where g i = g TOT ( V ci V c ) g i = effective green time for phase i (s), g TOT = total effective green time in the cycle (s), V ci = critical lane volume for phase I (tpc/h/ln), and V s = sum of the critical lane volumes (tpc/h). Equation 80 For the non-critical phase (and the movements served by these phases), the effective green time is set equal to the green time for the phase on the opposing approach that serves the same directional movement. The green time for each phase should be reviewed against policy requirements and other considerations such as the minimum green time and the time required for pedestrians to cross the approach. All green time and cycle length calculations should be adjusted to meet minimum requirements for all users. Step 6c: Compute capacity and v/c ratio The capacity c i and volume-to-capacity ratio X i for each lane group i are calculated using Equation 81 and Equation 82. c i = 1900 ( g i C ) 126 Equation 81

127 Equation 82 X i = v i c i where v i = volume for lane group i (pc/h) c i = capacity of lane group i (tpc/h/ln) g i = effective green time for lane group i (s), and C = cycle length (s). For the intersection as a whole, the critical degree of saturation X c is calculated using Equation 84. Equation 83 where v ci = volume for critical phase i (pc/h). X c = i=1 to n v ci c SUM The intersection capacity c SUM (tpc/h) is calculated using Equation 84. where c SUM = 1900 ( g ci = effective green time for critical phase i (s), and C = cycle length C (s). i=1 to n g ci C ) Equation 84 Step 7: Estimate Delay The control delay for each lane group d i (s/veh) is calculated using Equation 85. Equation 85 where d i = d 1 PF + d 2 127

128 d 1 = uniform delay (s), PF = progression adjustment factor, and d 2 = incremental delay term (s). The uniform delay d 1 (s/veh) is calculated using Equation 86. Equation 86 d 1 = 0.5C(1 g/c) 2 1 [min(1, X) (g/c)] where C = cycle length (s), g/c = effective green ratio, and X = volume-to-capacity ratio. The progression factor PF is given in Exhibit 59 and is selected based on the quality of progression from an upstream signalized intersection. Possible values for the progression factor are 0.70 if the quality of progression is good and 1.25 if the quality is poor. The default value is 1.00 if progression is average, indicating that vehicles arrive in a random manner. Exhibit 59: Progression Adjustment Factor Quality of Progression Progression Factor Good 0.70 Average (default) 1.00 Poor 1.25 The incremental delay d 2 (s/veh) is calculated using Equation 87. Equation 87 d 2 = 225 [(X 1) + (X 1) X cn ] where X = volume-to-capacity ratio, c = capacity (veh/h), and N = number of lanes. 128

129 Level of Service The level of service for each lane group or for the intersection is given in Exhibit 60 based on the average control delay. Note that if the volume-to-capacity ratio exceeds 1.0, then the level of service will be F regardless of the control delay. Exhibit 60: Level of Service, Signalized Intersections Level of Service A Control Delay (s/veh) 10 B >10 20 C >20 35 D >35 55 E >55 80 F >80 or X > 1.00 Adapted from Exhibit 18-4, 2010 HCM Queues The deterministic average queue for each lane group is determined by dividing the average uniform delay for that lane group by the capacity for that lane group. Equation 88 Where: Q = 3600 d 1 c Q = deterministic average queue for lane group (veh) d 1 = uniform delay for lane group (s) c = capacity per lane of lane group (veh/h/ln) The deterministic average queue for the lane group does not take into account random bunching of traffic arrivals within the analysis period. The deterministic average queue may be multiplied by 2.0 (approximately the ratio of the 95 th percentile to the mean for a Poison process) to obtain an approximation of the 95 th percentile longest queue likely to be observed each signal cycle. 129

130 6. WORKSHEETS The worksheets below illustrate how the computations might be laid out in a spreadsheet. Exhibit 61: Signalized Intersection Input Worksheet Volume Lanes PHF % HV Parking activity Ped activity LT phasing Signalized Intersection Planning Method, Input Worksheet (Part I) NB SB EB WB LT TH RT LT TH RT LT TH RT LT TH RT Exhibit 62: Signalized Intersection Calculations Part I Worksheet Signalized Intersection Planning Method, Calculations (Part I) Check #1 Check #2 Check #3 LT phasing E HVadj E PHF E LT E RT E P E LU v adj v i vc EW vc NS v c NB SB EB WB LT TH RT LT TH RT LT TH RT LT TH RT Step 1. Determine LT phasing Step 2. Convert turning movements to passenger car equivalents Step 3. Assign volumes to lane groups Step 4. Calculate critical lane groups Step 5. Intersection volume-to-capacity ratio v c/c i Intersection sufficiency 130

131 Exhibit 63: Signalized Intersection Calculations Part II Worksheet C L g TOT v ci v c g i c i X ij c SUM X c Signalized Intersection Planning Method, Calculations (Part II) NB SB EB WB LT TH RT LT TH RT LT TH RT LT TH RT Step 6. Calculate capacity Step 7. Estimate delay and level of service d 1 d2 PF d LOS d LOS Exhibit 64: Signalized Intersection Calculations Protected/Permitted Left Turn Worksheet g LTPT g LTPM E LTPT E LTPM E LTC V LTTOT V LTPT Signalized Intersection Planning Method, Protected-Permitted LT Worksheet NB SB EB WB 131

132 7. RELIABILITY ANALYSIS The 2010 HCM does not provide a method for estimating the variability of delay at a signal controlled intersection. The analyst might perform a sensitivity analysis by repeating the planning computations using the 25 th percentile and 75 th percentile highest demands of the year and the 25 th percentile and 75 th percentile highest capacities of the year (taking into account incidents) and report the results in a table such as shown below. Exhibit 65: Example Sensitivity Analysis Table for Signalized Intersection Reliability Average Delay (secs/veh) Demand Capacity 25 th Percentile Highest Median (50 th %) 75 th Percentile Highest 25 th % highest 50 th % (Median) 75 th % highest Table is intentionally blank. 8. MULTIMODAL LOS While vehicular delay invariably affect truck and transit LOS, the 2010 HCM does not provide a truck LOS measure or a transit LOS measure for signalized intersections. Procedures for evaluating street transit LOS at a signalized intersection are provided in Chapter 15 Pedestrians, Bicyclists, and Public Transit. The HCM does not provide procedures for assessing transit LOS at intersections. Analysts should consult the Transit Capacity and Quality of Service Manual [1]. 9. EXAMPLE Case Study II in Part IV provides an example application of the screening and simplified analysis methods described in this chapter. 10. REFERENCES 1. Transit Capacity and Quality of Service Manual, TCRP Report 165, Third Edition, Transportation Research Board, Washington, DC,

133 CHAPTER 13 STOP CONTROLLED INTERSECTIONS 1. OVERVIEW Stop-controlled intersections may be all-way stop controlled or partially stop controlled. A two-way stop intersection is an example of a partially stop controlled intersection. The HCM and this guide do not provide a method for intersections that fall in between 2-way stop and all-way stop control (e.g. threeway stops at four legged intersections) A two-way stop-controlled (TWSC) intersection is an intersection in which the movements on one street (labeled the minor street) are controlled by stop signs, while the movements on the other street (labeled the major street) are not stop controlled. An All-Way Stop-Controlled Intersection (AWSC) intersection is an intersection in which all movements are stop controlled. 2. APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Feasibility studies of: o Intersection Improvements Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW Intersection performance can be directly measured in the field or it can be estimated in great detail using microsimulation. However the resource requirements of both of these methods render them generally impractical for most planning and preliminary engineering applications (see Exhibit 66). Chapters 19 and 20 of the 2010 HCM provides a much less resource intensive approach to estimating intersection performance, however; it is generally impractical to use the HCM methods with 100% field measured inputs for many planning and preliminary engineering analyses. Employing the HCM methods with defaults identified in Chapter 19 and 20 of the 2010 HCM reduces the data requirements, but still requires specialized software to implement the complex computations. This chapter presents a simplified HCM mid-level method for evaluating all-way and two-way stop controlled intersections. 133

134 Exhibit 66: Analysis Options for Stop Controlled Intersections Data Needs & Limitations The data needs, assumptions, and limitations of each analysis approach are described below under the procedures for each approach. 4. SIMPLIFIED HCM METHOD FOR ALL-WAY STOP-CONTROLLED INTERSECTIONS An AWSC intersection is an intersection in which all movements are stop controlled. The operational analysis method for AWSC intersections, described in chapter 20 of the HCM 2010, uses an iterative approach to calculate the delay on one approach of the intersection, based on the flow rate on that approach and the flow rates on the other approaches. The method is complex enough to require a computational engine to produce the predictions of delay for even the most basic conditions. The planning method for AWSC intersections is based on the HCM operational analysis method. The method predicts the delay for each intersection approach and for the intersection. Because of the computational complexity of the operational analysis method, the planning method is presented in a series of figures from which the analyst can determine the approach delay and the intersection delay based on the volumes of the two intersecting streets and the number of lanes on each approach. Assumptions, Limitations and Input Requirements The following assumptions are made in applying the planning method for AWSC intersections: There are no pedestrians at the intersection There are one or two lanes on each approach Turning movements account for 20 percent of the traffic on each approach 134

135 The AWSC intersection planning method requires two inputs. The analyst is required to specify values for the volume for each movement and the number of lanes on each approach. Estimating V/C Ratio AWSC Intersections For the purposes of computing approximate volume to capacity ratios for the intersection, Exhibit 67 can be used. The capacity available to any single approach depends on how much capacity is consumed by the other approaches. Exhibit 67: Total Entering Capacity for AWSC Intersections Lanes on Street 1 Approach Lanes on Street 2 Approach Total Entering Capacity, All Approaches vph vph vph Adapted from equation 20-14, 2010 HCM, assuming average adjusted headways of 3 seconds for single lane approaches, two lane approaches increases capacity 50%. Estimating Delay AWSC Intersections The delay on each approach of an AWSC intersection is estimated by entering the street 1 (subject approach) approach volume and the maximum of the street 2 (cross street) approach volumes in Exhibit 68 for a single lane approach and using Exhibit 69 for a two or more lane approach. The delay for the street 1 volume is then read on the y-axis. The average intersection delay is then computed taking a weighted average of the approach delays. Equation 89 Where: d = average intersection delay (s/veh) v i = volume on approach i (veh/h) d i = delay on approach i (s/veh) d = v i d i v i 135

136 Exhibit 68: AWSC Intersection Planning Method, Street 1 Delay, 20% Turns, One-Lane Approaches Exhibit 69: AWSC Intersection Planning Method, Street 1 Delay, 20% Turns, Two-Lane Approaches 136

137 5. SIMPLIFIED HCM METHOD FOR TWO-WAY STOP-CONTROLLED INTERSECTION A TWSC intersection is an intersection in which the movements on one street (labeled the minor street) are controlled by stop signs, while the movements on the other street (labeled the major street) are not stop controlled. The planning method for TWSC intersections is based on the operational analysis method described in chapter 19 of the HCM The TWSC intersection planning method predicts the capacity and delay for all minor stream movements at a TWSC intersection. The method estimates the capacity of a minor stream movement based on the conflicting flows of higher priority traffic streams, and the critical headway and follow up headway of the minor traffic stream. Assumptions, Limitations & Data Requirements The planning method for TWSC intersections has the following limitations: There are no pedestrians at the intersection. There is no median barrier on the major street, so all gap acceptance processes from the minor street occur in one step. The flow on the major street arrives as a random process, with no platooning from any upstream traffic signals. An exclusive lane is provided for left-turning traffic on the major street. Short right turn lanes are not considered. U-turns are not considered. The TWSC intersection planning method requires four inputs. The demand volumes V i (veh/h) for each movement The proportion of heavy vehicles P HV for each movement The number of lanes (and the turn designation for each) on each approach, and The peak hour factor PHF for the intersection, either supplied by the analyst or assuming a default value of Estimating V/C Ratio TWSC Intersections The method includes eight steps, shown in Exhibit 70 and described below. 137

138 Exhibit 70: TWSC Intersection Planning Method, Computational Steps Step 1: Determine Movement Priorities Determine and label movements and priorities using the numbering scheme from Exhibit 71. The movements are ranked according to the following priorities. Rank 1 includes the through movements on the major street, movements 2 and 5. Rank 2 includes the major street left turn movements (1 and 4) and the minor street right turn movements. Rank 3 includes the minor street through movements (8 and 11). Rank 4 includes the minor street left turn movements (7 and 10). 138

139 Exhibit 71: Turning Movement Numbering for TWSC Intersection Step 2: Compute Flow Rates from Demands Convert movement demand volumes to flow rates using Equation 90. Equation 90 v i = V i PHF where v i = demand flow rate for movement i (veh/h) V i = demand volume for movement i (veh/h), and PHF = peak hour factor (default = 0.92) Step 3: Determine conflicting flow rates. Each non-rank 1 movement faces a unique set of conflicting flows through which the movement must maneuver. For example, a minor street through movement conflicts with one higher ranked movement (its opposing major street left turn movement) while the minor street left turn movement conflicts with up to three higher ranked movements (the major street left turn movements, the opposing minor street through movement, and the opposing minor street right turn movement). The conflicting flows (v c,x ) for each movement are calculated using the equations below. The demand flow rates (v i, where is ranges from 1 to 12 as per Exhibit 71) are the independent variables in each of these equations. Conflicting flows for the major street left turning movements (1 and 4) are calculated using Equation 91 and Equation 92: Equation 91 v c,1 = v 5 + v 6 139

140 Equation 92 v c,4 = v 2 + v 3 Conflicting flows for the minor street right turning movements (9 and 12) are calculated using Equation 93 through Equation 96 depending on the number of lanes on the major street: Two-lane major streets: Equation 93 v c,9 = v v 3 Equation 94 Four and six-lane major streets: v c,12 = v v 6 Equation 95 v c,9 = 0.5v v 3 Equation 96 v c,12 = 0.5v v 6 Conflicting flows for the minor street through movements (8 and 11) are calculated using Equation 96 and Equation 97: Equation 97 v c,8 = 2v 1 + v v 3 + 2v 4 + v 5 + v 6 Equation 98 v c,11 = 2v 4 + v v 6 + 2v 1 + v 2 + v 3 Conflicting flows for the minor street left turn movements (7 and 10) are calculated using Equation 99 through Equation 104 depending on the number of lanes on the major street: Two-lane major streets: Equation 99 v c,7 = 2v 1 + v v 3 + 2v 4 + v v v v

141 Equation 100 v c,10 = 2v 4 + v v 6 + 2v 1 + v v v v 8 Four-lane major streets: Equation 101 v c,7 = 2v 1 + v v 3 + 2v v v 11 Equation 102 Six-lane major streets: v c,10 = 2v 4 + v v 6 + 2v v v 8 Equation 103 v c,7 = 2v 1 + v v 3 + 2v v v 11 Equation 104 v c,10 = 2v 4 + v v 6 + 2v v v 8 Step 4: Determine critical headways and follow-up headways. Step 4a: Calculate the critical headway t c,x (s) for each movement x using Equation 105. Equation 105 t c,x = t c,base + t c,hv P HV where t c,base = base critical headways from Exhibit 71 (s), t c,hv = adjustment factor for heavy vehicles (1.0 for major streets with one lane in each direction; 2.0 for major streets with two or three lanes in each direction (s), P HV = proportion of heavy vehicles for movement (expressed as a decimal) Exhibit 72: Base Critical Headways Vehicle movement Two lanes Four lanes Six lanes Left turn from major street (1,4) Right turn from minor street (9,12) Through movement from minor street (8,11) Left turn from minor street (7,10) Step 4b: Calculate the follow up time t f,x (s) for each movement x using Equation

142 Equation 106 t f,x = t f,base + t f,hv P HV where t f,base = base follow up headway from Exhibit 73 (s), t f,hv = adjustment factor for heavy vehicles (0.9 for major streets with one lane in each direction, 1.0 for major streets with two or three lanes in each direction, and P HV = proportion of heavy vehicles for movement (expressed as a decimal). Exhibit 73: Base Follow Up Headways Vehicle movement Two lanes Four lanes Six lanes Left turn from major street (1,4) Right turn from minor street (9,12) Through movement from minor street (8,11) Left turn from minor street (7,10) Step 5: Calculate potential capacities. The potential capacity for movement x, c p,x, (veh/h) is calculated using Equation 107. where c p,x = v c,x e v c,xt c,x / e v c,xt f,x /3600 v c,x = conflicting flow rate for movement x (veh/h), t c,x = critical headway for movement x (s), and t f,x = follow up headway for movement x (s). Equation 107 Step 6: Calculate Movement Capacities. The movement capacity c m,j (veh/h) for the rank 2 movements j (major street left turn movements 1 and 4) and minor street right turn movements 9 and 12) is calculated using Equation 108. Equation 108 where c m,j = c p,j c p,j = potential capacity for rank 2 movement j = 1, 4, 9 or

143 The movement capacity c m,k (veh/h) for the rank 3 movements k (minor street though movements 8 and 11) is calculated using Equation 109 and Equation 110. Equation 109 where c m,8 = c p,8 (1 v 1 c m,1 ) (1 v 4 c m,4 ) c p,8 = potential capacity (veh/h) for movement 8, v 1 = volume for movement 1, v 4 = volume for movement 4, c m,1 = movement capacity for movement 1, and c m,4 = movement capacity for movement 4. Equation 110 where c m,11 = c p,11 (1 v 1 c m,1 ) (1 v 4 c m,4 ) c p,11 = potential capacity (veh/h) for movement 11, v 1 = volume for movement 1, v 4 = volume for movement 4, c m,1 = movement capacity for movement 1, and c m,4 = movement capacity for movement 4. The movement capacity c m,7 (veh/h) for the rank 4 movement 7 (minor street left turn movement) is calculated using Equation 111 and Equation 112. where c m,7 = (c p,7 )(p )(p 0,12 ) c p,7 (veh/h) = potential capacity for movement 7, p 0,12 = probability of queue free state for movement 12, and p is given by Equation 112. Equation

144 Equation 112 p = 0.65p " p " p " p" where p = p 0,1 p 0,4 p 0,11, the probability of queue free states for movements 1, 4, and 11. The movement capacity c m,10 (veh/h) for the rank 4 movement 10 (minor street left turn movement) is calculated using Equation 113 and Equation 114. where where c m,10 = (c p,10 )(p )(p 0,9 ) c p,10 (veh/h) = potential capacity for movement 10, p 0,9 = probability of queue free state for movement 9, and p is given by Equation 112. p = 0.65p " p " p " p" p = p 0,1 p 0,4 p 0,11, the probability of queue free states for movements 1, 4, and 11. Equation 113 Equation 114 Step 7: Calculate shared lane capacity c SH (veh/h) of the two minor street approaches using Equation 115. Equation 115 c SH = y v y v y y c m,y where v y = flow rate of movement y in the subject shared lane (veh/h), and c m,y = movement capacity of movement y in the subject shared lane (veh/h). 144

145 Delay TWSC Intersections Control delay d (s/veh) is calculated using Equation 116. Equation 116 d = T c m,x v x 1 + ( v 2 ( 3600 x 1) + c m,x c m,x [ c ) ( v x m,x c ) m,x 450T ] + 5 where: v x = flow rate for movement x (veh/h), c m,x = capacity of movement x (veh/h), T = analysis time period (default = 0.25 h) The approach control delay for all vehicles on an approach d A (s) is calculated using Equation 117. Equation 117 where d A = d rv r + d t v t + d l v l v r + v t + v l d r, d t, d l = computed control delay for the right-turn, through, and left-turn movements, (s/veh), and v r, v t, v l = flow rate of right-turn, through, and left-turn traffic on the approach, (veh/h). The intersection control delay is calculated using Equation 118. Equation 118 where d I = d A,1v A,1 + d A,2 v A,2 + d A,3 v A,3 + d A,4 v A,4 v A,1 + v A,2 + v A,3 + v A,4 d A,x = control delay on approach x (s/veh), and v A,x = flow rate on approach x (veh/h). 145

146 6. LEVEL OF SERVICE ANALYSIS (AWSC AND TWSC) The level of service ranges for stop-controlled intersections are given in Exhibit 74 based on control delay. Note that if the volume-to-capacity ratio exceeds one, the level of service will be F regardless of the control delay. Exhibit 74: Level of Service - Stop Controlled Intersections Control Delay (s/veh) X 1.0 X > A F >10 15 B F >15 25 C F >25 35 D F >35 50 E F >50 F F Adapted from exhibit 20-2, 2010 HCM 7. QUEUING ANALYSIS (AWSC AND TWSC) The deterministic average queue for each stop controlled approach at an intersection is determined by dividing the average delay for that approach by the capacity for that approach. Equation 119 Q = 3600 d c Where: Q = deterministic average queue on approach (veh) d = average delay on approach (s/veh) c = capacity of approach (veh/h) The deterministic average queue does not take into account bunching of vehicle arrivals within the analysis period. An approximate estimate of the stochastic 95 th percentile queue can be obtained by multiplying the deterministic average queue by 2.0 (the approximate ratio of the 95 th percentile to the mean for a Poisson process). For approaches with multiple lanes, the queue per lane can be estimated by dividing by the number of lanes, and applying an uneven lane usage adjustment factor to the result. 146

147 Equation 120 QPL = Q LU N Where: QPL = the queue per lane (veh/ln) Q = queue (veh) LU = uneven lane usage adjustment (decimal) (suggested default: 1.10) N = capacity of approach (veh/h) 147

148 8. WORKSHEETS The worksheets below illustrate how the computations might be laid out in a spreadsheet, and can be used to organize manual calculations, as desired. Exhibit 75: AWSC Intersection Delay Computation Worksheet All-Way Stop Control (AWSC) Intersection Planning Method Worksheet Approach NB SB EB WB Turning movement LT TH RT LT TH RT LT TH RT LT TH RT Volume Lanes Delay Delay Exhibit 76: TWSC Input Data Worksheet Two-Way Stop Control (TWSC) Intersection Planning Method, Input Data Worksheet Movements Demand Volume, V i Lanes PHF Flow rate, v i Proportion of heavy vehicles, P HV Exhibit 77: TWSC Capacity and Delay Computation Worksheet Two-Way Stop Control (TWSC) Intersection Planning Method, Capacity And Delay Worksheet Movements Flow rate, v i Conflicting flows, v c Critical headway, t c Follow up headway, t f Potential capacity, c p,x Movement capacity, c m,l Control delay, d Approach control delay, d A Intersection control delay, d i 148

149 9. RELIABILITY ANALYSIS The 2010 HCM does not provide a method for estimating the variability of delay at an intersection. The analyst might perform a sensitivity analysis by repeating the planning computations using the 25 th percentile and 75 th percentile highest demands of the year and the 25 th percentile and 75 th percentile highest capacities of the year (taking into account incidents) and report the results in a table such as shown below. Exhibit 78: Example Sensitivity Analysis Table for Intersection Reliability Average Delay (secs/veh) Demand Capacity 25 th Percentile Highest Median (50 th %) 75 th Percentile Highest 25 th % highest 50 th % (Median) 75 th % highest Table is intentionally blank. 10. MULTIMODAL LOS (NO METHOD AVAILABLE) The 2010 HCM does not provide a truck LOS measure for unsignalized intersections. The HCM does not provide procedures for assessing transit, bicycle, or pedestrian LOS at unsignalized intersections. Analysts should consult the Transit Capacity and Quality of Service Manual [1] for transit LOS analysis at intersections. 11. EXAMPLE (NONE PROVIDED) Resource limitations precluded development of an unsignalized intersection example application. 12. REFERENCES 1. Transit Capacity and Quality of Service Manual, TCRP Report 165, Third Edition, Transportation Research Board, Washington, DC,

150 CHAPTER 14 ROUNDABOUT INTERSECTIONS 1. OVERVIEW A roundabout is a circular intersection in which movements on the circle have the right-of-way. Movements entering the roundabout must yield to traffic already on the circle. The planning method for roundabouts is based on the operational analysis method described in chapter 21 of the HCM APPLICATIONS The procedures in this chapter are designed to support the following planning and preliminary engineering analyses: Feasibility studies of: o Intersection Improvements Land development traffic impact studies. 3. ANALYSIS METHODS OVERVIEW Intersection performance can be directly measured in the field or it can be estimated in great detail using microsimulation. However the resource requirements of both of these methods render them generally impractical for most planning and preliminary engineering applications (see Exhibit 79 ). Chapter 21 of the 2010 HCM provides a much less resource intensive approach to estimating intersection performance, however; it is generally impractical to use the HCM methods with 100% field measured inputs for many planning and preliminary engineering analyses. Employing the HCM methods with defaults identified in Chapter 21 of the 2010 HCM reduces the data requirements, but still requires specialized software to implement the complex computations. This chapter presents a simplified HCM mid-level method for evaluating roundabout controlled intersections. 150

151 Exhibit 79: Analysis Options for Stop Controlled Intersections 4. SIMPLIFIED HCM METHOD The roundabout planning analysis approach predicts the capacity and delay for each roundabout approach, and the delay for the intersection. The planning method is a simplification of the HCM operational analysis method. Data Needs Assumptions & Limitations The following limitations apply to the simplified HCM planning method for roundabouts: There are no pedestrians at the intersection By-pass lanes are not considered Only one or two lanes on the roundabout, and at the entries, are considered The roundabouts planning method requires four inputs: The volume for each movement, The number of lanes on each approach, The peak hour factor (default = 0.88 rural, 0.95 urban), and The proportion of heavy vehicles for each movement (default = 10% rural, 5% urban). Estimating V/C Ratio The roundabout planning method includes eight steps to estimate delay, shown in Exhibit 80 and described below. The first seven steps are executed to obtain the volume/capacity ratios. 151

152 Exhibit 80: Roundabout Planning Method Step 1: Estimate Flow Rates From Demands Convert movement demand volumes to flow rates using Equation 121. Equation 121 v i = V i PHF where v i = demand flow rate for movement i (veh/h), V i = demand volume for movement i (veh/h), and PHF = peak hour factor (default = 0.92) Step 2: Heavy Vehicle Adjustment Adjust flow rates for heavy vehicles using Equation 122 and Equation 123. Equation 122 v i,pce = v i f HV where 152

153 v i,pce = adjusted flow rate for movement i (veh/h), v i = demand flow rate for movement i (veh/h), and f HV is given by Equation 123. Equation 123 f HV = P T where P T = proportion of heavy vehicles for movement i. Step 3: Determine Circulating Flow Rate. The circulating flow rates v c,xx,pce are calculated for each leg of the roundabout using Equation 124 through Equation 127, where xx is the approach direction, either northbound (NB), southbound (SB), eastbound (EB), or westbound (WB). Equation 124 v c,nb,pce = v WBU,pce + v SBL,pce + v SBU,pce + v EBT,pce + v EBL,pce + v EBU,pce Equation 125 v c,sb,pce = v EBU,pce + v NBL,pce + v NBU,pce + v WBT,pce + v WBL,pce + v WBU,pce Equation 126 v c,eb,pce = v NBU,pce + v WBL,pce + v WBU,pce + v SBT,pce + v SBL,pce + v SBU,pce Equation 127 where v c,wb,pce = v SBU,pce + v EBL,pce + v EBU,pce + v NBT,pce + v NBL,pce + v NBU,pce v x,pce = adjusted flow rate for movement x (veh/h). Step 4: Determine entry flow rates by lane. For single-lane entries, the entry flow rate is the sum of all movement flow rates using that entry. For two-lane entries, the following procedure may be used to assign flows to each lane: 1. If only one lane is available for a given movement, the flow for that movement is assigned only to that lane. 153

154 1. The remaining flows are assumed to be distributed across the two lanes, subject to the constraints imposed by any designated or de facto lane assignments and any observed or estimated lane utilization imbalances. Five generalized multilane cases may be analyzed with this procedure. For cases in which a movement may use more than one lane, a check should first be made to determine what the assumed lane configuration may be. This may differ from the designated lane assignment based on the specific turning movement patterns being analyzed. These assumed lane assignments are given in Exhibit 81. For intersections with a different number of legs on each approach, the analyst should exercise reasonable judgment in assigning volumes to each lane. Exhibit 81: Assumed (De Facto) Lane Assignments Designated Lane Assignment Assumed Lane Assignment If v U + v L > v T + v R,e : L, TR (de facto left-turn lane) LT, TR L, LTR LTR, R Notes: If v R,e > v U + v L + v T : LT, R (de facto right-turn lane) Else LT, TR If v T + v R,e > v U + v L : L, TR (de facto through right lane) Else L, LTR If v U + v L + v T > v R,e : LT, R (de facto left through lane) Else LTR, R v U, v L, v T, and v R,e are the U-turn, left-turn, through, and nonbypass right-turn flow rates using a given entry, respectively. L = left, LT = left through, TR = through right, LTR = left through right, and R = right. On the basis of the assumed lane assignment for the entry and the lane utilization effect described above, flow rates can be assigned to each lane by using the formulas given in Exhibit 82. In this table, %RL is the percentage of entry traffic using the right lane, %LL is the percentage of entry traffic using the left lane, and %LL + %RL = 1. Exhibit 82: Volume Assignments for Two-Lane Entries Case Assumed Lane Assignment Left Lane Right Lane 1 L, TR v U + v L v T + v R,e 2 LT, R v U + v L + v T v R,e 3 LT, TR (%LL)v e (%RL)v e 4 L, LTR (%LL)v e (%RL)v e 5 LTR, R (%LL)v e (%RL)v e Notes: v U, v L, v T, and v R,e are the U-turn, left-turn, through, and right-turn flow rates using a given entry, respectively; L = left, LT = left through, TR = thro 154

155 Step 5: Determine the capacity of the entry lane c i in passenger car equivalents. The capacity of the entry lane is determined depending on the number of entry lanes and conflicting lanes using the appropriate equation given in Exhibit 83, where v c,pce (veh/h) is the conflicting flow rate for each entry. Exhibit 83: Capacity Equations for Roundabouts Entry Lanes Conflicting Lanes Capacity Equation 1 1 c e,pce = 1130e.003v c,pce 2 1 c e,pce = 1130e.003v c,pce 1 2 c e,pce = 1130e.007v c,pce 2 2 RL: c e,pce = 1130e.007v c,pce LL: c e,pce = 1130e.0075v c,pce Step 6: Convert Lane Rates to Flow Rates Convert lane flow rates and capacities into vehicles per hour using Equation 128. Equation 128 where v i = flow rate for lane i (veh/h) v i,pce = flow rate for lane i (pc/h), and f HV = heavy vehicle adjustment factor. v i = v i,pce f HV Equation 129 where c i = c i,pce f HV c i = capacity for lane i (veh/h), c i,pce = capacity for lane i (pc/h), and f HV = heavy vehicle adjustment factor for the lane. Step 7: Calculate V/C Ratios Calculate the volume-to-capacity ratio x i for each lane using Equation

156 Equation 130 x i = v i c i where v i = demand flow rate of the subject lane i (veh/h), and c i = capacity of the subject lane i (veh/h). For the purposes of computing approximate volume to capacity ratios for the intersection, Exhibit 67 can be used. The capacity available to any single approach depends on how much capacity is consumed by the other approaches. This assumes that through vehicles on opposing approaches do not enter intersection at same time. Delay The average control delay is computed in the following steps. Calculate Average Control Delay per Entry Lane Step 8a: Calculate average control delay d (s/veh) for each entry lane using Equation 131. Equation 131 where d = T c [ x 1 + ( 3600 (x 1) 2 c ) x m,x + 450T c = capacity of the subject lane (veh/h), T = duration of the analysis period (h) (default T = 0.25 h), and x = volume-to-capacity ratio of the subject lane. ] + 5(min [x, 1]) Calculate Average Control Delay per Approach Step 8b: Calculate the average control delay for each approach d approach (s/veh) using Equation 132. where d LL = delay for left lane (s/veh), v LL = volume in left lane (veh/h), d approach = d LLv LL + d RL v RL v LL + v RL Equation

157 d RL = delay for right lane (s/veh), and v RL = volume in right lane (veh/h). Calculate Intersection Average Control Delay Step 8c: Calculate the intersection control delay d intersection using Equation 133. Equation 133 d intersection = d iv i v i Where d i = control delay for approach I (s/veh), v i = flow rate for approach I (veh/h). Level of Service Analysis - Auto The level of service ranges are given in Exhibit 84 based on control delay. Note that if the volume-tocapacity ratio exceeds one, the level of service will be F regardless of the control delay. Exhibit 84: Level of Service, Roundabouts Control Delay (s/veh) X 1.0 X > A F >10 15 B F >15 25 C F >25 35 D F >35 50 E F >50 F F Adapted from exhibit 21-1, 2010 HCM Queuing Analysis The deterministic average queue for each approach at an intersection is determined by dividing the average delay for that approach by the capacity for that approach. Equation 134 Q = 3600 d c 157

158 Where: Q = deterministic average queue on approach (veh) d = average delay on approach (s/veh) c = capacity of approach (veh/h) The deterministic average queue does not take into account bunching of vehicle arrivals within the analysis period. An approximate estimate of the stochastic 95 th percentile queue can be obtained by multiplying the deterministic average queue by 2.0 (the approximate ratio of the 95 th percentile to the mean for a Poisson process). For approaches with multiple lanes, the queue per lane can be estimated by dividing by the number of lanes, and applying an uneven lane usage adjustment factor to the result. Where: QPL = Q LU N QPL = the queue per lane (veh/ln) Q = queue (veh) LU = uneven lane usage adjustment (decimal) (suggested default: 1.10) N = capacity of approach (veh/h) Equation

159 5. WORKSHEETS The worksheets below illustrate how the computations might be laid out in a spreadsheet, and can be used to organize manual calculations, as desired. Exhibit 85: Roundabout Input Worksheet Demand volume, V i Lanes Peak hour factor Demand flow rate, v i Roundabouts Planning Method, Input Worksheet NB SB EB WB LT TH RT LT TH RT LT TH RT LT TH RT Exhibit 86: Roundabout V/C and Delay Computation Worksheet Demand flow rate, v i Heavy vehicle adjustment factor, f HV Adjusted flow rate, v i,pce Circulating flow rates, v xx,pce Entry flow rates by lane, Capacity of entry lane, c i Lane flow rates Lane capacity Volume-tocapacity ratio, X Lane control delay, d Approach control delay, d Interstion control delay, d i Roundabouts Planning Method, Volume Adjustments NB SB EB WB LT TH RT LT TH RT LT TH RT LT TH RT NB- Lane 1 NB- Lane 2 SB- Lane 1 SB- Lane 2 EB- Lane 1 EB- Lane 2 WB- Lane 1 WB- Lane 2 159

160 6. RELIABILITY ANALYSIS The 2010 HCM does not provide a method for estimating the variability of delay at an intersection. The analyst might perform a sensitivity analysis by repeating the planning computations using the 25 th percentile and 75 th percentile highest demands of the year and the 25 th percentile and 75 th percentile highest capacities of the year (taking into account incidents) and report the results in a table such as shown below. Exhibit 87: Example Sensitivity Analysis Table for Intersection Reliability Average Delay (secs/veh) Demand Capacity 25 th Percentile Highest Median (50 th %) 75 th Percentile Highest 25 th % highest 50 th % (Median) 75 th % highest Table is intentionally blank. 7. MULTIMODAL LOS (NO METHOD AVAILABLE) The 2010 HCM does not provide a truck LOS measure for unsignalized intersections. The HCM does not provide procedures for assessing transit, bicycle, or pedestrian LOS at unsignalized intersections. Analysts should consult the Transit Capacity and Quality of Service Manual [1] for transit LOS analysis at intersections. 8. EXAMPLE (NONE PROVIDED) Resource limitations precluded development of an unsignalized intersection example application. 9. REFERENCES 1. Transit Capacity and Quality of Service Manual, TCRP Report 165, Third Edition, Transportation Research Board, Washington, DC,

161 CHAPTER 15 PEDESTRIANS, BICYCLISTS, AND PUBLIC TRANSIT 1. OVERVIEW In addition to providing performance measures and computational methods for the automobile mode, the HCM 2010 also provides a variety of measures for pedestrians and bicycles on various types of on- and off-street facilities. The HCM also provides a transit LOS measure for evaluating on-street public transit service in a multimodal context. A sister publication, the Transit Capacity and Quality of Service Manual (TCQSM, Kittelson & Associates et al. 2013), provides a variety of performance measures, computational methods, and spreadsheet tools to evaluate the capacity, speed, reliability, and quality of service of onand off-street transit service. The HCM s pedestrian and bicycle performance measures focus on (1) the impacts of other facility users on pedestrians and bicyclists and (2) facility design and operation features under the control of a transportation agency. However, some analyses may also be interested in the effects of urban design on pedestrians and bicyclists potential comfort and enjoyment while using a facility. In those cases, additional measures, such as the Walkability Index (Hall 2010) or the Bicycle Environment Quality Index (San Francisco Department of Public Health 2009), could be appropriate. This section is organized by HCM system element, providing guidance on applying the HCM and TCQSM s pedestrian, bicycle, and transit methods to a planning and preliminary engineering study. As research has not yet been conducted to quantify the pedestrian and bicycle experience for all types of HCM system elements, not every mode is addressed in each subsection below. 2. FREEWAYS Pedestrians and Bicycles In most cases, pedestrians and bicycles are prohibited on freeways; therefore, the operations and quality of service of these modes on freeways is not assessed. In some cases, a multiple-use path is provided within the freeway facility, with some sort of barrier separating non-motorized and motorized traffic. In these situations, the pedestrian and bicycle facility should be analyzed as an off-street pathway (see Section 9). In situations where bicycles are allowed on freeway shoulders, the HCM provides no guidance on evaluating performance. It is not recommended to use the HCM s multilane highways method for bicycles, as it was developed from urban street and suburban multilane highway data and has not been calibrated to freeway environments. 161

162 Transit Buses operating on freeways in level terrain will generally operate at the same speed as other vehicular traffic, although buses designed to primarily operate on urban streets may not have the power to travel at higher freeway speeds (e.g., over 55 mi/h). In addition, buses designed to primarily operate on urban streets may have poor performance on steep grades particularly when fully loaded with passengers and are recommended to be evaluated as a truck in these cases. Buses designed for freeway travel (i.e., motor coaches designed for long-distance trips) generally do not experience these issues. When bus routes stop along a freeway facility (e.g., at a stop or station in the freeway median or within a freeway interchange), the TCQSM can be consulted for guidance on estimating the delay associated with each stop. The TCQSM can also be consulted for performance measures for rail transit operating within a freeway right-of-way. 3. MULTILANE AND TWO-LANE HIGHWAYS Pedestrians When pedestrian facilities exist along a multilane highway (e.g., a sidewalk along a multilane highway in a suburban area), the facility can be analyzed as an urban street pedestrian facility (see Section M4). However, if the pedestrian facility is separated from a multilane or two-lane highway by a barrier, or is generally located more than 35 feet away from the travel lanes, it should be analyzed as an off-street facility (see Section 9). Lower-speed two-lane highways (posted speeds of 45 mi/h or less) can be evaluated using the urban street pedestrian method (see Section 4), whether or not a sidewalk exists. However, the HCM s urban street pedestrian method is not calibrated for, and not recommended for use with, higher-speed two-lane highways or multilane highways lacking sidewalks or side paths. Bicycles Chapter 15 of HCM 2010 provides a method for evaluating bicyclist perceptions of quality of service along multilane and two-lane highways. The method generates a bicycle LOS score, which can be translated into a bicycle LOS letter or used on its own. Exhibit 88 lists the required data for this method and provides suggested default values. Exhibit 88: Required Data for Multilane and Two-Lane Highway Bicycle Analysis Input Data (units) Suggested Default Value Speed limit (mi/h) Must be provided Directional automobile demand (veh/h)* Must be provided Number of directional lanes 1 (two-lane highway), 2 (multilane highway) Lane width (ft)* 12 Shoulder width (ft)* 6 Pavement condition rating (FHWA 5-point scale) 4 (good) Percentage of heavy vehicles (decimal)* 0.06** Peak hour factor (decimal)* 0.88 Percent of segment with occupied on-highway 0.00 parking 162

163 Notes: See HCM Chapter 15 for definitions of the required input data. *Also used by the multilane and/or two-lane highway LOS methods for automobiles. **HCM Chapter 26 provides state-specific default values. Of the inputs listed in Exhibit 88, the LOS result is highly sensitive to shoulder width and heavy vehicle percentage and is somewhat sensitive to lane width and pavement condition (particularly very poor pavement). The calculation of the bicycle LOS score is readily performed by hand, following the steps given in HCM Chapter 15, or can be easily set up in a spreadsheet. Transit The guidance presented above for transit operating on freeways (see Section 2) is also applicable to multilane and two-lane highways. 4. URBAN STREETS Pedestrians The HCM provides three pedestrian performance measures for urban street segments and facilities: space (reflecting the density of pedestrians on a sidewalk), speed (reflecting intersection delays), and a pedestrian LOS score (reflecting pedestrian comfort with the walking environment). Exhibit 89 lists the data required for these measures and provides suggested default values. Calculating the pedestrian LOS score requires a number of inputs. Most of these can be defaulted, and the ones that cannot be defaulted are used by the urban street automobile LOS method. Given that different pedestrian design standards are typically used for different combinations of roadway functional classifications and area types, it is recommended that analysts develop sets of default values covering the most common combinations for their study area, based on typical local conditions or design standards. Pedestrian space and speed are sensitive to effective sidewalk width, representing the portion of the sidewalk that is actually used by pedestrians. Common effective width reductions are 1.5 feet adjacent to the curb and 2.0 feet adjacent to a building face; HCM Exhibit and Exhibit provide effective width reductions for many other types of objects (e.g., street trees, street light poles, bus stop shelters, café tables). The effective width used for analysis purposes should be based on the narrowest point of the sidewalk from an effective width standpoint. As the types of objects that create effective width reductions will vary depending on the sidewalk design (e.g., use of landscape buffers, street tree presence) and the adjacent land uses, it is recommended that analysts develop a set of local effective width default values that cover the most common situations. 163

164 Exhibit 89: Required Data for Urban Street Pedestrian Analysis Input Data (units) For For For Default Value SPC SPD PLOS Sidewalk width (ft) 12 (CBD), 5 (other) Effective sidewalk width (ft) 8.5 (CBD), 3.5 (other) Bi-directional pedestrian volume (ped/h) Must be provided Free-flow pedestrian speed (ft/s) 4.4 Segment length (ft)* Must be provided Signalized intersection delay walking along See Section M5 or use street (s)* 12 (CBD), 30 (suburban) Signalized intersection delay crossing See Section M5 or use street (s)* 12 (CBD), 50 (suburban) Outside lane width (ft)* 12 Bicycle lane width (ft) 0 Shoulder/parking lane width (ft) 1.5 (curb and gutter only) 8 (parking lane provided) Percent segment with occupied on-street 0.00 (no parking lane) parking (decimal) 0.50 (parking lane provided) Street trees or other barriers (yes/no) a No Landscape buffer width (ft) 0 (CBD), 6 (other) Curb presence (yes/no) Yes Median type (divided/undivided) Undivided Number of travel lanes* Must be provided Directional vehicle volume (veh/h)* Must be provided Vehicle running speed (mi/h)* See Section H5 or use the posted speed Intersection pedestrian LOS score Calculated, see Section M5 (unitless) Average distance to nearest signal (ft) One-third the segment length Notes: See HCM Chapter 17 for definitions of the required input data. SPC = space, SPD = speed, PLOS = pedestrian level of service, CBD = central business district. *Input data used by or calculation output from the HCM urban street automobile LOS method. a Street trees, bollards, or other similar vertical barriers 3 ft or more tall with a spacing of 20 feet or less, or a continuous barrier at least 3 ft tall. Pedestrian Space Pedestrian space (or its reciprocal, density) is an important consideration in areas that can experience high pedestrian volumes (e.g., CBDs, highly touristed areas, areas around special event venues). Pedestrian space is calculated using the following equations: v p = v ped 60W E 164

165 Equation 136 S p = ( v p 2 )S pf 0.5S pf Equation 137 A p = 60 S p v p Equation 138 where v p = pedestrian flow per unit width of sidewalk (ped/ft/min), v ped = pedestrian flow rate in the subject sidewalk (walking in both directions) (ped/h), W E = effective sidewalk width (ft), S p = pedestrian walking speed (ft/s), S pf = free-flow pedestrian walking speed (ft/s), and A p = pedestrian space (ft 2 /ped). The pedestrian space result can be converted into a LOS letter. The HCM uses the worse of the two LOS letters from pedestrian space and the pedestrian LOS score as the basis for establishing LOS for an urban street link (i.e., a section of urban street between signalized intersections). The pedestrian space LOS letter can be determined using the top row of HCM Exhibit 17-3 (i.e., ignoring the pedestrian LOS score value). Under typical circumstances, pedestrian space LOS does not control the result until hourly pedestrian volumes are well in excess of 1,000 per hour. Pedestrian Speed Average pedestrian speed can be calculated for a link (between signalized intersections) using Equation 2 above and for a segment (including delay at the downstream signalized intersection) by combining the travel time to walk the length of the segment with the average delay experienced at the downstream intersection, as given in Equation 139. It is assumed that pedestrians experience no delay when crossing unsignalized cross-streets or driveways while walking between signalized intersections. Therefore, average speed for a segment is L S Tp,seg = L + d S pp p Equation 139 where S Tp,seg = travel speed of through pedestrians for the segment (ft/s), L = segment length (ft), S p = pedestrian walking speed (ft/s) from Equation 2, and 165

166 d pp = average pedestrian delay when walking parallel to the segment (s/p). Section 5 can be used to estimate typical pedestrian delay values when walking parallel to the segment, based on typical street widths and traffic signal timings for a given area, or a default value from Exhibit 11 can be applied. Pedestrian LOS Score The HCM provides a pedestrian LOS score (and associated LOS letter) for urban street links (between signalized intersections), segments (a link plus the downstream intersection), and facilities (multiple contiguous segments) that relates to pedestrian perceptions of quality of service for each element. The pedestrian LOS score uses the same scale as related bicycle and transit LOS scores, and an auto traveler perception score, allowing for multimodal analyses in which the relative quality of service of each travel mode can be evaluated and compared to each other. At present, at a facility level, the HCM methodology only evaluates signalized urban streets, and not streets with all-way stops, roundabouts, or interchanges. However, the link methodology can be used to evaluate pedestrian facilities along any urban street section between intersections. As noted above, the pedestrian LOS methodology requires a number of input values, but most of these can be defaulted, particularly when local default values have been established for different combinations of roadway functional class and area type. The calculations can be performed by hand or (preferably when large numbers of segments will be evaluated) incorporated into a spreadsheet. HCM Equations through are used to calculate a link LOS score. This score can be converted to a LOS letter and reported by itself, if the purpose of the analysis is to evaluate the pedestrian environment between intersections. Otherwise, the analyst can proceed to calculate a segment LOS score. The segment LOS score combines the link LOS score and the signalized intersection LOS score (see Section 5), weighting the two scores by the relative amounts of time that pedestrians experience each element. It is calculated using HCM Equation A roadway crossing difficulty factor also enters into this equation. This factor incorporates the lesser of the delays pedestrians experience when (1) trying to cross the street at an unsignalized midblock location (if legal), or (2) walking to the nearest traffic signal, crossing the street, and walking back on the other side of the street. The segment LOS score can be converted to a LOS letter and reported by itself (using HCM Exhibit 17-3), if the purpose of the analysis is to evaluate the pedestrian environment along a street segment, including intersection and streetcrossing effects. Otherwise, the analyst can proceed to calculate a facility LOS score. The facility LOS score is calculated similarly to the segment LOS score, weighting the LOS scores of the individual links and signalized intersections that form the facility by the relative amounts of time that pedestrians experience each element. It is calculated using HCM Equation Bicycles The HCM provides two bicycle performance measures for urban street segments and facilities: average travel speed (reflecting intersection delays) and a bicycle LOS score (reflecting bicyclist comfort with the 166

167 bicycling environment). Exhibit 90 lists the data required for these measures and provides suggested default values. As can be seen in Exhibit 90, calculating the bicycle LOS score requires a number of inputs. Most of these can be defaulted, and the ones that cannot be defaulted are used by the urban street automobile LOS method. Given that different bicycle design standards are typically used for different combinations of roadway functional classifications and area types, it is recommended that analysts develop sets of default values covering the most common combinations for their study area, based on typical local conditions or design standards. Exhibit 90: Required Data for Urban Street Bicycle Analysis Input Data (units) For For Default Value SPD BLOS Bicycle running speed (mi/h) 12 Signalized intersection delay (s) See Section M5 or use 10 (CBD), 22 (suburban) Segment length (ft)* Must be provided Bicycle lane width (ft)** 5 (if provided) Outside lane width (ft)** 12 Shoulder/parking lane width (ft)** 1.5 (curb and gutter only) 8 (parking lane provided) Percent segment with occupied onstreet parking (decimal)** 0.50 (parking lane provided) 0.00 (no parking lane) Pavement condition rating (1 5) 3.5 Curb presence (yes/no)** Yes Median type (divided/undivided)** Undivided Number of travel lanes* Must be provided Directional vehicle volume (veh/h)* Must be provided Vehicle running speed (mi/h)* See Section H5 or use the posted speed Percent heavy vehicles (%)* 3% Access points on the right side 17 (urban arterial), 10.5 (suburbuan (points/mi) arterial), 30.5 (urban collector), 24 (suburban collector) Intersection bicycle LOS score (unitless) Calculated, see Section M5 Notes: See HCM Chapter 17 for definitions of the required input data. SPD = speed, BLOS = bicycle level of service, CBD = central business district. *Input data used by or calculation output from the HCM urban street automobile LOS method. **Input data used by the HCM urban street pedestrian LOS method. 167

168 Bicycle Speed Average bicycle speed can be calculated for a segment given an assumed bicycle running speed along the segment, the segment length, and the average delay at the downstream intersection, as given in the equation below. S Tb,seg = 3,600L 5,280(t Rb + d b ) Equation 140 where S Tb,seg = travel speed of through bicycles along the segment (mi/h), L = segment length (ft), t Rb = segment running time of through bicycles = (3,600 L)/(5,280 S b ) (s), S b = bicycle running speed along the link (mi/h), and d b = average bicycle control delay at the intersection (s). Section 5 can be used to estimate typical bicycle delay values at intersections, based on typical traffic signal timings for a given area, or a default value from Exhibit 90 can be applied. Bicycle LOS Score The HCM provides a bicycle LOS score (and associated LOS letter) for urban street links (between signalized intersections), segments (a link plus the downstream intersection), and facilities (multiple contiguous segments) that relates to bicyclist perceptions of quality of service for each element. The bicycle LOS score uses the same scale as related pedestrian and transit LOS scores, and an auto traveler perception score, allowing for multimodal analyses in which the relative quality of service of each travel mode can be evaluated and compared to each other. At present, at a facility level, the HCM methodology only evaluates signalized urban streets, and not streets with all-way stops, roundabouts, or interchanges. However, the link methodology can be used to evaluate bicycle facilities along any urban street section between intersections. As noted above, the bicycle LOS methodology requires a number of input values, but most of these can be defaulted, particularly when local default values have been established for different combinations of roadway functional class and area type. The calculations can be performed by hand or (preferably when large numbers of segments will be evaluated) incorporated into a spreadsheet. HCM Equations through are used to calculate a link LOS score. This score can be converted to a LOS letter and reported by itself, if the purpose of the analysis is to evaluate the bicycling environment between intersections. Otherwise, the analyst can proceed to calculate a segment LOS score. The segment LOS score combines the link LOS score and the signalized intersection LOS score (see Section 5), weighting the two scores by the relative amounts of time that bicyclists experience each element. It is calculated using HCM Equation The number of access points per mile on the right 168

169 side of the road (e.g., driveways, unsignalized cross-streets) also enters into this equation as a factor that causes discomfort to bicyclists. The segment LOS score can be converted to a LOS letter and reported by itself (using HCM Exhibit 17-4), if the purpose of the analysis is to evaluate the bicycling environment along a street segment, including intersection and access point effects. Otherwise, the analyst can proceed to calculate a facility LOS score. The facility LOS score is calculated similarly to the segment LOS score, weighting the LOS scores of the individual links and signalized intersections that form the facility by the relative amounts of time that bicyclists experience each element. It is calculated using HCM Equation Transit The HCM provides a transit LOS score (reflecting passenger comfort as they walk to a bus stop, wait for a bus, and ride on the bus. In addition, the TCQSM (Kittelson & Associates 2013) provides the most up-todate methods for calculating bus capacities and average bus speeds on urban streets. Exhibit 91 lists the data required for these measures and provides suggested default values. 169

170 Exhibit 91: Required Data for Urban Street Transit Analysis Input Data (units) For For For Default Value CAP SPD TLOS Dwell time at the critical stop (s) 60 (CBD, major transfer point), 30 (urban), 15 (suburban) Average dwell time along facility (s) 45 (CBD), 20 (urban), 15 (suburban) Coefficient of variation of dwell times 0.60 (decimal) Through traffic g/c ratio at the critical stop 0.45 (CBD), 0.35 (other) (decimal)* Curb lane v/c ratio at the critical stop s Must be provided intersection* (decimal) Busiest stop location (online/offline) Offline Clearance time at the critical stop (s) 10 (online stop, near-side stop with queue jump, stops where yield-to-bus laws are obeyed) 14 (far-side or midblock offline stop) 25 (near-side offline stop) Number of loading areas at the critical 1 stop Design failure rate (%) 10% (CBD), 2.5% (other), 25% (when calculating speed, TLOS) Traffic blockage adjustment factor 0.89 (decimal) Bus frequency (bus/h) Must be provided Average bus stop spacing (stops/mi) 8 (CBD), 6 (urban), 4 (suburban) Posted speed limit (mi/h)* Must be provided Average bus acceleration rate (ft/s 2 ) 3.4 Average bus deceleration rate (ft/s 2 ) 4.0 Bus lane type (4 categories) Mixed traffic Traffic signal progression (3 categories) Typical Average passenger load factor (p/seat) Must be provided Average excess wait time (min) 3 Percent stops with shelter (%) 25% Percent stops with bench (%) 25% Average passenger trip length (mi) 3.7 Pedestrian LOS score (decimal)** See Exhibit 11 or use 3.50 Notes: See the TCQSM for definitions of the required input data. CAP = capacity, SPD = speed, TLOS = transit level of service, CBD = central business district. *Input data used by or calculation output from the HCM urban street automobile LOS method. **Calculation output from the HCM pedestrian LOS method. 170

171 Bus Capacity Bus capacity reflects the number of buses per hour that can serve the critical bus stop along a facility, at a desired level of reliability. The critical bus stop is typically the bus stop with the highest dwell time (i.e., serves the greatest number of passengers), but a lower-passenger-volume stop with low green times for bus movements or a stop at an intersection with high right-turning traffic volumes can also be the critical stop. It is calculated using the equations below, adapted from the TCQSM: 3,600(g/C) B = N el f tb t c + t d (g/c) + Zc v t d Equation 141 f tb = 1 f l ( v cl c cl ) Equation 142 where B = bus capacity (bus/h); N el = number of effective loading areas at a bus stop, from Exhibit 92; f tb = traffic blockage adjustment factor (decimal); 3,600 = number of seconds in 1 hour; g/c = ratio of effective green time to total traffic signal cycle length (decimal); t c = clearance time (s); t d = average (mean) dwell time (s); Z = standard normal variable corresponding to a desired failure rate, from Exhibit 93; c v = coefficient of variation of dwell times (decimal); f l = bus stop location factor (decimal), from Exhibit 94; v cl = curb lane traffic volume at intersection (veh/h); and c cl = curb lane capacity at intersection (veh/h). When more than one bus can use the critical bus stop at a time (i.e., more than one loading area is provided), the bus stop s capacity will be greater than if only loading area was provided. Exhibit 92 gives the number of effective loading areas for a given number of physical loading areas, for both online (buses stop in the travel lane) and offline (buses stop out of the travel lane) stops. 171

172 Exhibit 92: Efficiency of Multiple Loading Areas at Bus Stops Number of Physical Loading Areas Number of Effective Loading Areas Online Stops Source: Adapted from TCQSM Exhibit Offline Stops Exhibit 93 provides values for Z, the standard normal variable, for different failure rates the percentage of time that a bus will arrive at a bus stop only to have to wait for other buses to finish serving their passengers before space opens up for the arriving bus to enter the stop. Capacity is maximized when a queue of buses exists to move into a bus stop as soon as other buses leave, but this situation would cause significant bus delays and schedule reliability problems. Therefore, a lower design rate is normally used as an input, balancing capacity with operational reliability. However, the TCQSM s method for estimating bus speed is calibrated to maximum capacity and therefore uses a 25% (maximum practical) failure rate in its calculation. Exhibit 93: Values of Z Associated with Given Failure Rates Design Failure Rate Z 1.0% % % % % % % % Source: TCQSM Exhibit

173 The location of the critical bus stop relative to the nearest intersection and the ability of buses to avoid right-turning traffic influences capacity. Exhibit 94 gives values for the bus stop location factor f l used in Equation 142. Exhibit 94: Bus Stop Location Factor Values Bus Stop Location Buses Restricted to Right Lane Bus Freedom to Maneuver Buses Can Use Right Turns Prohibited Adjacent Lane or Dual Bus Lanes Near side of intersection Middle of the block Far side of intersection Source: Adapted from TCQSM Exhibit Bus Speed Two options are provided for planning-level estimates of bus speeds along urban streets: 1. If only a planning estimate of bus speeds is desired, then Option 1 can be followed. This option requires less data and is faster to calculate. It accounts for traffic and traffic signal delays in a generalized way. 2. If it is desired to estimate both automobile and bus speeds, then Option 2 can be followed. This option applies the same basic method used for automobiles, but makes adjustments to reflect (a) overlapping signal delay time and bus dwell time to serve passengers, (b) bus delays waiting to re-enter the traffic stream, and (c) bus congestion at bus stops when more than half of the facility s bus capacity is being used. Option 1: Generalized Bus Speed Method This option is based on the TCQSM s bus speed estimation method. In this option, bus speeds are calculated in four steps. First, an unimpeded bus travel time rate, in minutes per mile, is calculated for the condition in which a bus moves along a street without traffic or traffic signal delays, with the only source of delay being stops to serve passengers. Second, additional delays due to traffic and traffic signals are estimated. Third, the bus travel time rate is converted to an equivalent speed. Finally, the speed is reduced to reflect the effects of bus congestion. The unimpeded bus travel time rate is based on the posted speed, the number of stops per mile, the average dwell time per stop, and typical bus acceleration and deceleration rates. It is calculated as follows: t u = t rs + N s (t dt + t acc + t dec )

174 Equation 143 t acc = 1.47v run a Equation 144 t dec = 1.47v run d Equation L ad = 0.5at acc + 0.5dt dec Equation 146 L rs = 5,280 N s L ad 0 Equation 147 L rs t rs = 1.47v run Equation 148 where t u = unimpeded running time rate (min/mi), t rs = time spent at running speed (s/mi), N s = average stop spacing (stops/mi), t dt = average dwell time of all stops within the section (s/stop), t acc = acceleration time per stop (s/stop), t dec = deceleration time per stop (s/stop), 60 = number of seconds per minute, 1.47 = conversion factor (5,280 ft/mi / 3,600 s/h), v run = bus running speed on the facility (typically the posted speed) (mi/h); a = average bus acceleration rate to running speed (ft/s 2 ), d = average bus deceleration rate from running speed (ft/s 2 ), L ad = distance traveled at less than running speed (ft/stop), L rs = distance traveled at running speed per mile (ft/mile), 5,280 = number of feet per mile, and L ad = distance traveled at less than running speed (ft/stop). If the calculated length traveled at running speed in Equation 147 is less than zero, then the bus cannot accelerate to the input running speed before it must begin decelerating to the next stop. In this case, the calculation sequence must be performed again with a lower running speed selected. 174

175 Next, additional bus travel time delays (t l, in minutes per mile) are estimated directly from Exhibit 95, using the bus facility type, traffic signal progression quality, and area type as inputs: Exhibit 95: Estimated Bus Running Time Losses on Urban Streets (min/mi) Condition Bus Lane Bus Lane, No Right Turns Bus Lane With Right Turn Delays Bus Lanes Blocked by Traffic Mixed Traffic Flow CENTRAL BUSINESS DISTRICT Typical Signals set for buses Signals more frequent than bus stops ARTERIAL ROADWAYS OUTSIDE THE CBD Typical Adapted from TCQSM Exhibit Third, the unimpeded bus travel time rate and the additional bus travel time delays are added together to obtain a base bus travel time rate, which is then converted into a base bus speed: t r = t u + t l S b = 60 t r Equation 149 Equation 150 where t r = base bus running time rate (min/mi), t u = unimpeded running time rate (min/mi), t l = additional running time losses (min/mi), 60 = number of minutes in an hour, and S b = base bus speed (mi/h). Finally, a bus bus interference factor is estimated from Exhibit 96, using the bus volume-to-maximum capacity ratio as an input. This factor reflects delays caused by buses blocking other buses that wish to enter or leave a stop (e.g., bus stop failure). Maximum bus capacity is determined by using a 25% failure rate when computing bus capacity. The base bus speed is multiplied by the bus bus interference factor to obtain the estimate of average bus travel speed along the facility. As can be seen in Exhibit 96, bus 175

176 speeds are only reduced when at least half of a facility s maximum bus capacity is scheduled. Under typical conditions and if bus stops can only serve one bus at a time (i.e., one loading area per stop), at least buses per hour need to be scheduled before bus speeds are affected. Exhibit 96: Bus Bus Interference Factor Values Bus Volume-to- Maximum Capacity Ratio Bus Bus Interference Factor < Source: TCQSM Exhibit S bus = S b f bb Equation 151 where S bus S b f bb = average bus speed along facility (mi/h), = base bus speed (mi/h), and = bus bus interference factor (decimal). Option 2: Modified Auto Speed Method This option modifies the auto speed estimation method for segments with signalized intersections (see Sections 5 and 4) to reflect additional delays experienced by buses and to account for potentially overlapping traffic signal delay and dwell time delay. The auto Equation for estimating segment travel time is modified as follows for buses: T i,bus = 5,280 FFS 3,600 L i + d int,bus + d mb + d bs 176

177 Equation 152 where T i,bus = base bus travel time for segment i (s), FFS = midblock free-flow speed from (mi/h), 5,280 = number of feet per mile, 3,600 = number of seconds per hour, L i = distance from upstream intersection stop bar to downstream intersection stop bar for segment i (ft), d int,bus = average bus traffic signal delay not part of dwell time from Equation 159 (s), d mb = midblock bottleneck delay (if any) (s), and d bs = total bus stop delay in the segment (s). Total bus stop delay in the segment is calculated as follows: d bs = N s (t dt + t acc + t dec + t re ) Equation 153 where d bs = total bus stop delay in the segment (s), N s = number of bus stops in the segment (stops), t dt = average dwell time per stop (s/stop), t acc = bus acceleration time per stop (s/stop), t dec = bus deceleration time per stop (s/stop), t re = average re-entry delay per stop (s/stop) = t cl 10, and t cl = average clearance time per stop (s/stop). When applying Equation 153, the number of bus stops in the segment includes all mid-block stops and any bus stop associated with the downstream intersection (even if far-side and technically located in the next segment). Similarly, any bus stop associated with the upstream intersection is excluded from the count of bus stops. Average bus speed in the segment is calculated as follows: 3,600 L i S i,bus = f 5,280 T bb i,bus Equation 154 where S i,bus = average bus speed for segment i including all delays (mi/h), L i = distance from upstream intersection stop bar to downstream intersection stop bar for segment i (ft), T i,bus = base bus travel time for segment i (s), and 177

178 f bb = bus bus interference factor (decimal) from Exhibit 96. Average facility bus speed is calculated as follows: S bus = 3,600 L i 5,280 T i,bus Equation 155 where S bus = average bus speed along facility (mi/h), L i = distance from upstream intersection stop bar to downstream intersection stop bar for segment i (ft), 5,280 = number of feet per mile, 3,600 = number of seconds per hour, T i,bus = base bus travel time for segment i (s). Transit LOS Score The HCM provides a transit LOS score (and associated LOS letter) for urban street segments (a link plus the downstream intersection) and facilities (multiple contiguous segments). The segment score relates to transit passengers experiences walking to or from bus stops in the segment, waiting for buses at bus stops in the segment, and riding on buses within the segment. The transit LOS score uses the same scale as related pedestrian and bicycle LOS scores, and an auto traveler perception score, allowing for multimodal analyses in which the relative quality of service of each travel mode can be evaluated and compared to each other. The calculations can be performed by hand or (preferably when large numbers of segments will be evaluated) incorporated into a spreadsheet. HCM Equations through are used to calculate a link LOS score. This score can be converted to a LOS letter and reported by itself (using HCM Exhibit 17-4), if the purpose of the analysis is to evaluate transit conditions within a segment. Otherwise, a facility score is calculated by weighting the LOS scores of the individual segments that form the facility by the relative length of each segment. It is calculated using HCM Equation The transit LOS score is particularly sensitive to the bus frequency provided as an input and is somewhat sensitive to the average bus speed and passenger load factor provided as inputs. 178

179 Quick Screening MMLOS Methods for Urban Streets The service volume tables in this section can be used to look up the street transit, bicycle and pedestrian LOS for urban streets. The reader will note that transit, bicycle, and pedestrian levels of service are generally more sensitive to the transit service provided and the physical features of the street than they are to motor vehicle traffic volumes. However, the analyst may use these tables to quickly assess the effects of vehicular traffic on level of service based on the general characteristics of the street and the bus service provided on the street. Transit Service Volume Tables As can be seen in Exhibit 97, street transit LOS is highly sensitive to the frequency of transit service provided, with the speed of the service having an important, but lesser effect on transit LOS. Therefore, vehicle traffic volumes, which primarily affect transit speeds, do not greatly affect transit LOS, except to the extent that high volumes might prevent transit agencies from providing the promised frequency of service (see Exhibit 98). 179

180 Exhibit 97: Sensitivity of Bus LOS to Frequency and Speed Bus Frequency LOS A-C LOS D LOS E LOS F 1 bus/hr N/A N/A >35 mph <30 mph 2 buses/hr >25 mph mph 3-10 mph <3 mph 3 buses/hr >11 mph 4-11 mph <4 mph N/I 4 buses/hr >7 mph 2-7 mph <2 mph N/I Notes: - Table does not apply to CBD bus operations. Applies to streets with posted speed limits in range of 35 to 45 mph with 50% of bus stops with shelters and benches, sidewalks. - N/A = not achievable - The LOS thresholds vary slightly depending on the posted speed limit of the street (which affects the pedestrian environment. - N/I = low bus speeds no longer sufficient to cause LOS E/F at these frequency levels Exhibit 98: Transit LOS Maximum Auto Volume Table Area Type Buses/h Speed Limit (mi/h) Maximum Directional Auto Volume for Target Transit LOS (veh/h/ln) LOS A-C LOS D LOS E CBD Urban Urban Suburban Suburban 1 45 N/A N/A 720 Notes: Assumptions: - N/A = Not Achievable, which indicates that target transit LOS cannot be achieved for given assumed transit service, even at zero auto volumes - Entries are vehicles per hour per lane in single direction. - Excess wait time 2 minutes - Average passenger trip length 3 miles - Average passenger load is 85% seated capacity - 50% of bus stops have shelters and benches - Five foot sidewalks present - Traffic signals coordinated o 120 second cycle o 45% g/c o Left turn pockets, left turn phases. 180

181 Three Through Lanes Two Through Lanes One Through Lane Lanes 6' Bike lane 50% Parking 85% Parking LOS A-C LOS D LOS E LOS A-C LOS D LOS E LOS A-C LOS D LOS E LOS A-C LOS D LOS E Bicycle Service Volume Tables A bicycle service volume table for a range of urban street conditions is provided in Exhibit 99. Exhibit 99: Bicycle LOS Maximum Auto Volume Table 55 mph PSL 45 mph PSL 35 mph PSL 25 mph PSL ** ** ** 210 ** ** 330 ** ** 890 ** ** ** ** ** 330 ** ** 510 ** ** 680 ** ** ** ** ** ** ** ** ** ** ** ** 280 ** ** 740 ** ** ** ** ** 430 ** ** 670 ** ** 1780 ** ** ** ** ** 670 ** ** 1020 ** ** 1370 ** ** ** ** ** ** ** ** ** ** ** ** 560 ** ** 1490 ** ** ** ** ** 640 ** ** 1010 ** ** 2670 ** ** ** ** ** 1000 ** ** 1530 ** ** 2050 ** ** ** ** ** ** ** ** ** ** ** ** 850 ** ** 2240 ** ** Notes: - Entries are maximum vehicles per hour per lane in single direction allowable for target bicycle LOS. - PSL is posted speed limit. - 50% and 85% parking refer to the percentage of curb space occupied by a parked vehicle. - ** indicates that auto volumes would have to exceed capacity of signalized intersection to cause bicycle LOS to degrade further - N/A indicates that target bicycle LOS cannot be achieved even at zero auto volumes 181

182 6' Bike lane 50% Parking 6' Buffer 5' Sidewalk LOS A-C LOS D LOS E LOS A-C LOS D LOS E Pedestrian Service Volume Tables Exhibit 100 provides a pedestrian service volume table a range of urban street conditions with posted speed limits of 45 and 55 miles per hour. Exhibit 101 provides a similar table for urban streets with posted speed limits of 25 and 35 miles per hour. Note that for the lower speed streets, the quality of the pedestrian facilities outweighs the effects of the vehicular traffic volumes. For 25 mph and 35 mph posted speed limit streets with sidewalks, parking, and bike lanes, no amount of auto traffic will cause the pedestrian level of service to be worse the LOS C (given the assumptions built into these tables). Exhibit 100: Pedestrian LOS Maximum Auto Volume Table Higher Speed Streets 55 mph PSL 45 mph PSL N/A N/A N/A v/c> v/c> v/c>1 580 v/c>1 v/c> v/c> v/c> v/c> v/c> v/c>1 720 v/c>1 v/c>1 620 v/c>1 v/c>1 800 v/c>1 v/c> v/c>1 680 v/c>1 v/c>1 580 v/c>1 v/c>1 760 v/c>1 v/c> v/c> v/c> v/c>1 620 v/c>1 v/c>1 600 v/c>1 v/c>1 780 v/c>1 v/c>1 670 v/c>1 v/c>1 840 v/c>1 v/c>1 Notes: - Entries are maximum vehicles per hour per lane in single direction allowable for target pedestrian LOS. - PSL is posted speed limit - 50% parking indicates that 50% of the available curb space is occupied by parked vehicles. - v/c>1 indicates that auto volumes would have to exceed capacity of signalized intersection to cause pedestrian LOS to degrade further - N/A = not achievable, which indicates that target pedestrian LOS cannot be achieved even at zero auto volumes 182

183 6' Bike lane 50% Parking 6' Buffer 5' Sidewalk LOS A-C LOS D LOS E LOS A-C LOS D LOS E Exhibit 101: Pedestrian LOS Maximum Auto Volume Table Lower Speed Streets 35 mph PSL 25 mph PSL N/A v/c> v/c>1 610 v/c>1 v/c>1 670 v/c>1 v/c>1 720 v/c>1 v/c>1 780 v/c>1 v/c> v/c>1 630 v/c>1 v/c>1 700 v/c>1 v/c>1 750 v/c>1 v/c>1 860 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 820 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 900 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 660 v/c>1 v/c>1 710 v/c>1 v/c>1 770 v/c>1 v/c>1 820 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 v/c>1 Notes: - Entries are maximum vehicles per hour per lane in single direction allowable for target pedestrian LOS. - PSL is posted speed limit. - 50% parking indicates that 50% of the available curb space is occupied by parked vehicles. - v/c>1 indicates that auto volumes would have to exceed capacity of signalized intersection to cause pedestrian LOS to degrade further - N/A = not achievable, which indicates that target pedestrian LOS cannot be achieved even at zero auto volumes 183

184 5. SIGNALIZED INTERSECTIONS Pedestrians The HCM provides two pedestrian performance measures suitable for planning analyses of signalized intersections: average pedestrian delay and a pedestrian LOS score that reflects pedestrian comfort while crossing an intersection. Exhibit 102 lists the data required for these measures and provides suggested default values. The HCM also provides calculation methods for assessing intersection corner circulation area and crosswalk circulation area, but these typically require more detailed data than would be available for a planning analysis. Exhibit 102: Required Data for Signalized Intersection Pedestrian Analysis Input Data (units) For For Default Value DEL PLOS Traffic signal cycle length (s)* 60 (CBD), 120 (suburban) Major street WALK time (s) See Section D3 or use 19 (CBD), 31 (suburban), 7 (minimum) Minor street WALK time (s) See Section D3 or use 19 (CBD), 7 (suburban), 7 (minimum) Number of lanes crossed on minor Must be provided street crosswalk* Number of channelizing islands crossed 0 on minor street crosswalk 15-minute volume on major street Must be provided (veh)* Number of major street through lanes in Must be provided the direction of travel* Mid-block 85th percentile speed on Posted speed limit major street (mi/h) Right-turn on red flow rate over the 0 (right turns on red prohibited) minor street crosswalk (veh/h) Must be provided (otherwise) Permitted left-turn volume over the 0 (protected left-turn phasing) minor street crosswalk (veh/h) 10% of through 15-minute volume (permitted left-turn phasing) 5% of through 15-minute volume (protected-permitted left-turn phasing) Notes: See HCM Chapter 18 for definitions of the required input data. DEL = delay, PLOS = pedestrian level of service, CBD = central business district. *Input data used by or calculation output from the HCM urban street automobile LOS method. Pedestrian Delay Average pedestrian delay for a given crosswalk is calculated as follows: d p = (C g Walk) 2 2C 184

185 Equation 156 where d p = average pedestrian delay (s), C = cycle length (s), and g Walk = effective walk time for the crosswalk (s). Pedestrian LOS Score The HCM provides a method (Equations through 18-77) for calculating a pedestrian LOS score (and associated LOS letter using HCM Exhibit 18-5) for signalized intersections. This score can be used on its own or integrated into the urban street pedestrian LOS procedures. Most of the method s inputs are required by the auto LOS method for signalized intersections or can be defaulted. An exception is the right-turn-on-red flow rate over the crosswalk being analyzed. The LOS score is sensitive to this input and a wide range of values are possible for it. The HCM recommends developing local default values for this variable for use in planning analyses. Bicycles The HCM provides two bicycle performance measures for signalized intersections: average bicycle delay and a bicycle LOS score that reflects bicyclist comfort while crossing an intersection. Exhibit 103 lists the data required for these measures and provides suggested default values. Exhibit 103: Required Data for Signalized Intersection Bicycle Analysis Input Data (units) For For Default Value DEL BLOS Traffic signal cycle length (s)* 60 (CBD), 120 (suburban) Effective green time for bicycles (s) Effective green time for parallel through automobile traffic* 15-minute bicycle flow rate (bicycles/h) Must be provided 15-minute automobile flow rate Must be provided (veh/h)* Cross-street width (ft) Must be provided Bicycle lane width (ft) 5 (if provided) Outside lane width (ft)* 12 Shoulder/parking lane width (ft) 1.5 (curb and gutter only) 8 (parking lane provided) Percent of intersection approach and 0.00 (no parking lane) departure with occupied on-street 0.50 (parking lane provided) parking (decimal) Number of parallel through lanes Must be provided (shared or exclusive)* Notes: See HCM Chapter 18 for definitions of the required input data. DEL = delay, BLOS = bicycle level of service, CBD = central business district. *Input data used by or calculation output from the HCM urban street automobile LOS method. 185

186 Bicycle Delay When bicyclists share the lane with automobile traffic, bicyclist delay is the same as automobile delay and can be calculated using Equation 157 (see section 4). When bicyclists have their own lane, bicycle delay is calculated as follows: d b = 0.5C(1 g b/c) 2 1 min [ v bic c, 1.0] g b b C c b = s b g b C Equation 157 Equation 158 where d b = average bicycle delay (s), g b = effective green time for the bicycle lane (s), C = cycle length (s), v bic = bicycle flow rate (bicycles/h), c b = bicycle lane capacity (bicycles/h), and s b = bicycle lane saturation flow rate (bicycles/h) = 2,000. Bicycle LOS Score The HCM provides a method (Equations through 18-84) for calculating a bicycle LOS score (and associated LOS letter using HCM Exhibit 18-5) for signalized intersections. This score can be used on its own or integrated into the urban street bicycle LOS procedures. Most of the method s inputs are required by the auto LOS method for signalized intersections or can be defaulted. Transit The HCM does not provide a transit LOS score for signalized intersections; the impacts of signalized intersections on bus speeds are incorporated into the segment and facility LOS scores (see Section 4). The following is a procedure for estimating the additional delay that buses experience at intersections waiting for a green light once the buses are finished serving passengers. Because a portion of the dwell time often overlaps with the signal delay time, it is necessary to split out the portion of signal delay that occurs after dwell time is completed. This procedure assumes that a bus stop exists in the vicinity of the signalized intersection; otherwise, bus signal delay is equivalent to automobile signal delay. When a bus stop exists in the intersection vicinity, average bus signal delay is estimated using the equations below. The input values are the same as those required for computing automobile signal delay (see Section 4). d int,bus = d 1,bus + d 2 186

187 Equation 159 d 1,bus = (1 g C g ) C 2 Equation 160 where d int,bus = average bus traffic signal delay not part of dwell time (s), d 1,bus = uniform bus delay (s), d 2 = incremental delay term from Equation 51 (s), g = effective green time (s), and C = cycle length (s). 6. STOP-CONTROLLED INTERSECTIONS Pedestrians Two-Way Stops and Midblock Crossings The HCM 2010 provides a method for estimating pedestrian delay crossing the major street at two-way stop-controlled intersections and at midblock crosswalks. Exhibit 104 lists the required data. Exhibit 104: Required Data for Two-Way Stop-Controlled Intersection Pedestrian Delay Calculation Input Data (units) Default Value Crosswalk length (ft) Must be provided Average pedestrian walking speed (ft/s) 3.5 Pedestrian start-up time and end clearance time (s) 3 Number of through lanes crossed Must be provided Vehicle flow rate during the peak 15 min (veh/s) Must be provided; note the units of veh/s Notes: See HCM Chapter 19 for definitions of the required input data. When a pedestrian refuge area is available in the street median, pedestrians can cross the street in two stages. In this case, delay should be calculated separately for each stage of the crossing and totaled to determine the overall delay. First, pedestrian delay is calculated for the scenario in which motorists do not yield to pedestrians (i.e., pedestrians must wait for a suitable gap in traffic). This calculation neglects the additional delay that occurs when pedestrian crossing volumes are high enough that pedestrian platoons form (i.e., some pedestrians have to wait for the pedestrians ahead of them to step off the curb before they can enter the crosswalk). The following equations are used: t c = L S p + t s 187

188 Equation 161 t c v P b = 1 e N L Equation 162 P d = 1 (1 P b ) N L Equation 163 d g = 1 v (evt c vt c 1) Equation 164 d gd = d g P d Equation 165 where t c = critical headway for a single pedestrian (s), S p = average pedestrian walking speed (ft/s), L = crosswalk length (ft), t s = pedestrian start-up time and end clearance time (s), P b = probability of a blocked lane (i.e., an approaching vehicle at the time the pedestrian arrives at the crosswalk that prevents an immediate crossing), P d = probability of a delayed crossing, N L = number of through lanes crossed, v = vehicular flow rate (veh/s). d g = average pedestrian gap delay (s), d gd = average gap delay for pedestrians who incur nonzero delay. When motorists yield to pedestrians, pedestrian delay is reduced. The average pedestrian delay in this scenario is calculated as follows: n d p = h(i 0.5)P(Y i ) + (P d P(Y i )) d gd i=1 n i=1 Equation 166 where d p i = average pedestrian delay (s), = sequence of vehicle arrivals after the pedestrian arrives at the crosswalk, 188

189 n = average number of vehicle arrivals before an adequate gap is available = Int(d gd /h), h = average vehicle headway for each through lane (s), and P(Y i ) = probability that motorist i yields to the pedestrian, from Exhibit 105. The motorist yielding rate M y is an input to the equations in Exhibit 105, and all other variables in the exhibit are as defined previously. Yielding rates for a selection of pedestrian crossing treatments are given in HCM Exhibit Alternatively, local values can be developed from field observations. Exhibit 105: Equations for Calculating Probability of Vehicles Yielding to a Crossing Pedestrian Lanes Crossed 1 Probability of Vehicle i Yielding P(Y i ) = P d M y (1 M y ) i 1 Equation 167a i 1 2 P(Y i ) = [P d P(Y j )] [ (2P b[1 P b ]M y ) + (P 2 b M 2 y ) ] P Equation 167b d i 1 j=0 3 P(Y i ) = [P d P(Y j )] [ P b 3 M 3 y + 3P 2 b (1 P b )M 2 y + 3P b (1 P b ) 2 M y ] P Equation 167c d j=0 4 P(Y i ) i 1 = [P d P(Y j )] j=0 [ P b 4 M y 4 + 4P b 3 (1 P b )M y 3 + 6P b 2 (1 P b ) 2 M y 2 + 4P b (1 P b ) 3 M y P d ] Equation 167d All-Way Stops The HCM 2010 provides a qualitative discussion of contributors to pedestrian delay at all-way STOPcontrolled intersections. However, the research base does not exist to provide a calculation method. Bicycles The HCM 2010 provides qualitative discussions of bicycle delay at two-way and all-way STOP-controlled intersections. However, the research base does not exist to provide calculation methods. Transit Buses will experience the same amount of control delay as other motor vehicles at these intersections. 7. ROUNDABOUTS Pedestrian delay at roundabouts can be estimated using the methods for two-way STOP-controlled intersections (see Section 6). The HCM provides no quantitative method for estimating bicycle delay, although it can be expected to be similar to vehicular delay, if bicyclists circulate as vehicles, or to 189

190 pedestrian delay, if bicyclists dismount and use the crosswalks. Buses will experience the same amount of control delay as other motor vehicles. 8. INTERCHANGE RAMP TERMINALS The HCM does not provide methods for estimating pedestrian or bicycle delay at interchange ramp terminals, although pedestrian delay could be estimated by evaluating each element along a pedestrian facility (e.g., signalized crosswalk, crosswalk over an otherwise free-flowing ramp terminal) separately. Buses will experience the same amount of control delay as other motor vehicles, unless they stop between two signalized ramp terminals and lose the benefit of any traffic signal timing designed to progress vehicles through the interchange. 9. OFF-STREET PATHWAYS The HCM 2010 provides LOS measures for three combinations of modes and facility types: Pedestrians on an exclusive off-street pedestrian facility, Pedestrians on a shared-use path, and Bicyclists on an exclusive or shared off-street facility. Exhibit 106 lists the required data for analyzing each of these situations. 190

191 Exhibit 106: Required Data for Off-Street Pathway Analysis Input Data (units) For For For Default Value PEX PSH BIKE Facility width (ft) Must be provided Effective facility width (ft) Same as facility width Pedestrian volume (ped/h) Must be provided Bicycle volume (bicycles/h) Must be provided Total path volume (p/h) Must be provided Bicycle mode split (%) 55% of path volume Pedestrian mode split (%) 20% of path volume Runner mode split (%) 10% of path volume Inline skater mode split (%) 10% of path volume Child bicyclist mode split (%) 5% of path volume Peak hour factor (decimal) 0.85 Directional volume split (decimal) 0.50 Average pedestrian speed (ft/min) 300 Average pedestrian speed (mi/h) 3.4 Average bicycle speed (mi/h) 12.8 Average runner speed (mi/h) 6.5 Average inline skater speed (mi/h) 10.1 Average child bicyclist speed (mi/h) 7.9 SD of pedestrian speed (mi/h) 0.6 SD of bicycle speed (mi/h) 3.4 SD of runner speed (mi/h) 1.2 SD of inline skater speed (mi/h) 2.7 SD of child bicyclist speed (mi/h) 1.9 Segment length (mi) Must be provided Walkway grade 5% (yes/no) Yes Pedestrian flow type (random/platooned) Random Centerline stripe presence (yes/no) No Source: Default values from Hummer et al. (2006), except for effective facility width. Notes: See HCM Chapter 23 for definitions of the required input data. PEX = pedestrian LOS on an exclusive path, PSH = pedestrian LOS on a shared path, BIKE = bicycle LOS on all off-street pathways, SD = standard deviation. 191

192 Pedestrians on an Exclusive Off-Street Facility Pedestrian LOS on an exclusive facility is based on the average space available to pedestrians. It is calculated using the following three equations: v 15 = v h 4 PHF v p = v W E A p = S p v p Equation 168 Equation 169 Equation 170 where v 15 = pedestrian flow rate during peak 15 min (p/h), v h = pedestrian demand during analysis hour (p/h), PHF = peak hour factor, v p = pedestrian flow per unit width (p/ft/min), W E = effective facility width (ft), A p = average pedestrian space (ft 2 /p). S p = average pedestrian speed (ft/min). Average pedestrian space is converted into an LOS letter using HCM Exhibit 23-1 (for random pedestrian flow) or HCM Exhibit 23-2 (when pedestrian platoons form). HCM Exhibit can be used to estimate the reduction in average pedestrian speed that occurs when walkway grades exceed 5%. The LOS result is highly sensitive to the average pedestrian speed provided as an input. Pedestrians on a Shared Off-Street Facility Pedestrian LOS on a shared off-street facility is based on the number of times per hour an average pedestrian meets or is passed by bicyclists using the path. The weighted number of meeting and passing events is calculated as follows: F p = Q sb PHF (1 S p S b ) 192

193 Equation 171 F m = Q ob PHF (1 + S p S b ) Equation 172 F = (F p + 0.5F m ) Equation 173 where F p = number of passing events (events/h), F m = number of meeting events (events/h), Q sb = bicycle demand in same direction (bicycles/h), Q ob = bicycle demand in opposing direction (bicycles/h), PHF = peak hour factor, S p = mean pedestrian speed on path (mi/h), S b = mean bicycle speed on path (mi/h), and F = weighted total events on path (events/h). Average pedestrian space is converted into an LOS letter using HCM Exhibit The LOS result is sensitive to the peak hour factor provided as an input. Bicyclists on an Off-Street Facility Bicycle LOS on all types of off-street facilities is based on a bicycle LOS score that considers: The average number of times per minute a bicyclist meets or is overtaken by other path users, The path width, The presence or absence of a centerline stripe, and The average number of times per minute a bicyclist is delayed in passing another path user (for example, because an oncoming path user is in the way). At a minimum, total path width and the total number of hourly path users must be provided, although results will be more accurate if the actual mode split of path users (bicyclists, pedestrians, runners, inline skaters, and child bicyclists) is known or can be defaulted using local values. The bicycle LOS score is particularly sensitive to the bicycle mode split, the peak hour factor, and the directional distribution provided as inputs, and somewhat sensitive to whether or not a centerline stripe is present. HCM Exhibit 23-5 is used to convert the bicycle LOS score into an LOS letter. The calculation process requires a large number of computations, and the use of a computational engine is recommended. The FHWA project (Hummer et al. 2006) that developed the method developed an engine, which can be downloaded from 193

194 pedbike/05138/sharedusepathstloscalculator.xls. The FHWA computational engine applies the peak hour factor in a different order in the computational sequence than the HCM implementation of the method does. However, any difference between the two methods is negligible for planning purposes. 10. REFERENCES Hall, R. A. HPE s Walkability Index Quantifying the Pedestrian Experience. In Compendium of Technical Papers, ITE 2010 Technical Conference and Exhibit, Savannah, Ga., March Highway Capacity Manual Transportation Research Board of the National Academies, Washington, D.C., Hummer, J. E., N. M. Rouphail, J. L. Toole, R. S. Patten, R. J. Schneider, J. S. Green, R. G. Hughes, and S. J. Fain. Evaluation of Safety, Design, and Operation of Shared-Use Paths Final Report. Report FHWA-HRT Federal Highway Administration, Washington, D.C., July Kittelson & Associates, Inc.; Parsons Brinckerhoff; KFH Group, Inc.; and Texas A&M Transportation Institute. TCRP Report 165: Transit Capacity and Quality of Service Manual, 3rd Edition. Transportation Research Board of the National Academies, Washington, D.C., San Francisco Department of Public Health. Bicycle Environmental Quality Index (BEQI) Draft Report. San Francisco, Calif., June

195 CHAPTER 16 TRUCK LEVEL OF SERVICE The 2010 HCM does not provide a truck LOS measure. NCFRP 41 does provide a truck LOS measure. [1] 1. THE TRUCK LEVEL OF SERVICE INDEX Truck level of service is defined as a measure of the quality of service provided by a facility for truck hauling of freight as perceived by shippers and carriers. It is measured in terms of the percentage of ideal conditions achieved by the facility for truck operations. A logistic function is used to compute the percentage of ideal conditions achieved by the facility for truck operations. Where: %TLOS = 1 ( e 200x ) Equation 174 %TLOS X = The truck LOS index as a percentage of ideal conditions = Truck Utility Function Ideal conditions are defined as a facility usable by trucks with legal size and weight loads, with no atgrade railroad crossings, that provides reliable truck travel at truck free-flow speeds, at low cost (no tolls). Reliable performance is defined as 100% probability of on-time arrival for the truck. A facility is considered to deliver 100% probability of on-time arrival as long as its travel time index for trucks falls below 1.33 for uninterrupted facilities and 3.33 for interrupted flow facilities (These values are approximately the auto LOS E/F thresholds for these facility types). The truck travel time index is the ratio of the truck free flow speed to the actual truck speed. Truck free-flow speed is defined as the maximum sustainable speed that an average truck can achieve under low traffic flow conditions given the prevailing grades, exclusive of intersection delays. The Truck Utility Function A truck utility function is used for computing the truck LOS index. Where: U(x) = A (POTA 1) + B (TTI 1) + C (Toll mi) + D (TFI 1) Equation 175 U(x) = Utility of facility for truck shipments 195

196 A B C D POTA TTI Toll/mi TFI = shipping distance sensitive weighting parameter for reliability = 5/ASL Where: ASL = average shipment length (200 miles for Continental US, 280 miles for Alaska, 30 miles for Hawaii) (miles) = a free-flow speed sensitive weighting parameter for shipment time = -0.32/FFS, Where: FFS = truck Free-Flow Speed (mi/h) = a weighting parameter for shipment cost = = a weighting parameter for truck friendliness of facility = 0.03 = Probability of On-Time Arrival, with on-time being defined as a TTI of 1.33 or less for freeways, multi-lane highways, and 2-lane highways. For urban streets TTI <=3.33. = Travel Time Index for study period, ratio of truck free-flow speed to actual truck speed. = Truck toll charged per mile ($/mi). Volume weighted average for all truck types. = Truck Friendliness Index (1.00 = no constraints or obstacles to legal truck load and vehicle usage of facility, 0.00 = no trucks can use facility) The utility function is weighted so that facilities with truck friendliness indices of 0.60 or less will always yield LOS F regardless of the speed or reliability of the facilities. Truck LOS Thresholds The truck LOS index is the ratio of the utility for actual conditions over the utility for ideal conditions. The truck LOS index is converted into an equivalent letter grade based on its freight facility class, according to the thresholds given in Exhibit 107. The thresholds for a given letter grade are higher for the higher class facilities. Exhibit 107: Truck LOS Model Service Measure and Thresholds LOS Class I Class II Class III Primary Freight Facility Secondary Facility Tertiary Facility A >=90% >=85% >=80% B >=80% >=75% >=70% C >=70% >=65% >=60% D >=60% >=55% >=50% E >=50% >=45% >=40% F <50% <45% <40% LOS = Level of Service. Entries are the percent achievement of ideal facility operating conditions for trucks. MAP-21, the Moving Ahead for Progress in the 21st Century Act (P.L ), requires the Department of Transportation to establish a national freight network to assist States in strategically directing resources toward improved movement of freight on highways (Federal Register, 2013)[2]. A tentative three class system (shown in Exhibit 108) employing some of the general criteria outlined in MAP-21 is 196

197 recommended for classifying highway facilities by their relative importance to the region s and national economy. 2. ESTIMATION OF ON-TIME ARRIVAL FROM TTI If the cumulative distribution of travel time indices for the facility is available, it is a simple matter for the analyst to read the probability of on time arrival for any selected on-time arrival threshold (for example, the threshold might be defined as 1.33 times the free-flow travel time) (see Exhibit 109). If only the median (50 th %) and 95 th percentile TTI s are available to the analyst then the probability of on-time arrival for a selected target TTI (e.g. 1.10) can be approximated using a fitted Burr Distribution (Burr, 1942). 4 Where: P(TTI) = cumulative probability of TTI TTI = desired target travel time index P(TTI) = 1 (1 + TTI c ) k c, -k = distribution parameters, both greater than zero Equation 176 Solving for the value of TTI that represents a certain cumulative percentile of the distribution: (Taylor & Susilawati, 2012) 5 c TTI(P) = (1 P) 1 k 1 Equation 177 Where: TTI(P) = Percentile (P) of TTI Thus the median (50 th ) and 95 th percentile TTI s are: c TTI(50%) = (2) 1 k 1 4 Burr, I. (1942). Cumulative frequency functions. Annals of Mathematical Statistics, 13, Taylor, M. A., & Susilawati. (2012). Using The Burr Distribution For Measuring Travel Time Reliability. Proceedings of the 5th International Symposium on Transportation Network Reliability. Hong Kong, China. 197

198 Equation 178 c TTI(95%) = (20) 1 k 1 Equation 179 The two equations (Equation 178,Equation 179) are solved for the two unknowns: k and c. One then uses these values of k and c plus the agency s target on-time arrival threshold TTI to estimate the probability of on-time arrival. Exhibit 108: Facility Freight Classification System Facility Class Description Suggested Criteria Examples I Highway facility critical to the inter-regional or within region movement of goods Facility carries a high volume of goods by truck (by tonnage or by value). Trucks may account for a high volume or percentage of AADT compared to other facilities in the region. Interstate freeway, interregional rural principal arterial. II Highway facility of secondary importance to goods movement within or between regions. Facility carries lesser volumes of goods (by tonnage or value). Trucks account for a lesser volume or percentage of AADT. Urban principal arterial, Connector to major intermodal facilities (maritime port, intermodal rail terminal, airports) III Highway facility of tertiary importance to goods movement within or between regions. Connectors to significant single origins/destinations of goods, such as major manufacturing facilities, sources of raw materials (mines, oil, etc.). Connectors to truck service facilities and terminals Access roads to mines, energy production facilities, factories, truck stops, truck terminals. 3. A SERVICE-TTI LOOKUP TABLE FOR TRUCK LOS The estimation of truck level of service can be expedited by estimating the average peak hour mixed auto and truck speed. Making an adjustment to the mixed traffic speed to get the truck speed, one can then apply the SHRP2-C11 equation to estimate the 95 th percentile peak hour speed for trucks. From this information plus other assumed defaults, one can then construct a Service-TTI look up table for trucks on freeways and highways, and urban streets. The average peak hour truck TTI is estimated from the peak hour auto speed by applying a local adjustment factor to reflect local driving characteristics. 198

199 TTI(Truck) = TTI(mixed) f LA Equation 180 Where: TTI(truck) = the truck travel time index TTI(mixed) = the ratio of the free-flow speed to the actual speed for mixed auto and truck traffic. f LA = the local adjustment factor to account for local truck driving behavior (selected at discretion of analyst). The analyst enters Exhibit 109 for the appropriate facility type and free flow speed (for urban streets only) using the computed truck TTI for average peak hour conditions (interpolation OK). The table shows the estimated 95th percentile TTI, the estimated probability of on-time arrival (POTA), the estimated utility for trucks, and the %TLOS index. The letter grade level of service is then read off for the appropriate facility class. 4. REFERENCES 1. Dowling, R., G. List, B. Yang, E. Witzke, A. Flannery, Final Report, NCFRP Project 41, Incorporating Truck Analysis into the Highway Capacity Manual, Transportation Research Board, Washington, DC, Federal Register. (2013, February). Federal Register, 78(25),

200 FFS = 35 mi/h Signalized Urban Streets FFS = 45 mi/h FFS = 55 mi/h Freeways and Rural Highways Exhibit 109: Truck TTI Level of Service Look Up Table Truck TTI 95% TTI POTA Utility %TLOS Class I Class II Class III % % A A A % % B A A % % C B B % % D D C % % E E D % % F F E % % F F F % % F F F % % B A A % % B A A % % B B A % % C B B % % D C C % % E D D % % F F E % % B A A % % B A A % % B B A % % C C B % % D D C % % F E E % % F F F % % B A A % % B B A % % C B B % % D C C % % E E D % % F F F % % F F F 200

201 PART III HIGH LEVEL ANALYSES The chapters in this part of the Guide describe high-level analysis methods that work best when evaluating highway systems at an area-wide level. These methods enable the analyst to cover large geographic areas with hundreds of miles of highways very efficiently. The methods presented here cover monitoring existing system performance as well as forecasting future performance. 201

202 CHAPTER 17 CORRIDOR QUICK ESTIMATION SCREENLINE ANALYSIS 1. INTRODUCTION Transportation planners assess future investments in a corridor based on the performance of the freeways and streets that make up the corridor transportation system. The performance of the corridor system and its components are often estimated through a travel demand and analysis forecasting process combined with either microscopic or macroscopic traffic operations model. This process requires a variety of inputs and outputs, which the HCM can provide, including capacity, queues, delay, travel speeds, and level of service. Note that the consistency of defaults across facilities in a corridor should be considered. This chapter presents a high level quick estimation method for quickly assessing Exhibit 110: Example Corridor Screenlines available corridor capacity. More detailed corridor analyses would employ the high level methods described in the following chapter, or they would employ the midlevel methods described earlier in Part II 2. SCREENING FOR CAPACITY AND MULTIMODAL LOS HOT SPOTS For the purposes of quickly screening the corridor for multimodal level of service problem (hot) spots one can divide the corridor into a set of screenlines where the demands are checked against HCM service volume tables for auto, transit, bicycle, and pedestrian level of service (see Exhibit 110). The screenlines are located by the analyst at key points, particularly choke points in the corridor. For example, in the illustration, Screenlines numbers 1, and 6 are located at key choke points in the corridor with the fewest parallel facilities available to carry traffic. The other screenlines are located at spots where corridor demand may significantly change from section to section (often between freeway interchanges). The forecasted AADT for each freeway or major surface street crossing the screenline is compared to the values in the appropriate service volume table for each mode to assess whether facility is likely to operate at a level of service acceptable to the agency. 202

203 Note that the use of screenlines will not catch intersection problem spots, so key intersections should be checked as well. The screenline analysis may indicate sections of the corridor where high vehicle volumes suggest that the intersections should be checked for potential LOS problems. Exhibit 111 illustrates a set of corridor screenline checks for the freeway and arterial corridor shown in Exhibit 110. Exhibit 111: Example Corridor Screenlines V/C and LOS Checks AADT/Lane v/c Screening Freeway Multimodal LOS screening Arterial Screen Freeway Arterial Freeway Arterial Corridor Auto LOS Auto LOS Transit LOS Bike LOS Ped LOS 1 16,500 3,300 82% 21% 55% LOS D LOS C LOS D LOS C LOS C 2 16,100 4,800 80% 30% 58% LOS D LOS C LOS D LOS C LOS C 3 20,900 7, % 46% 78% LOS F LOS D LOS D LOS D LOS D 4 16,600 6,600 82% 42% 64% LOS D LOS D LOS D LOS D LOS D 5 17,300 3,500 86% 22% 58% LOS D LOS C LOS D LOS C LOS C 6 13,900 n/a 69% n/a 69% LOS C n/a n/a n/a n/a n/a = not applicable (arterial not present). Freeway capacity at 20,200 AADT/lane, Arterial capacity at 15,900 AADT/lane. AADT s computed for K = 0.10, D = Service volume tables from Chapters 8, 11,

204 CHAPTER 18 AREAS AND SYSTEMS 1. OVERVIEW Transportation planners assess future investments based on the performance of the freeways and streets that make up a regional transportation system. The performance of the system and its components are often estimated through a travel demand and analysis forecasting process. This process requires a variety of inputs, which the HCM can provide, including prediction of travel speeds. The procedure is performed for all of the highway subsystems in five steps. - First the necessary input data is assembled. - Then the free-flow speed of the links is computed. - The capacity of each link is then computed. - Then the mean link speeds are computed. - Finally the travel time and other performance measures are computed for all the links and summed for each subsystem. Look-up tables of capacity and free-flow speed defaults can be used to short-cut two of the steps (Steps 2 and 3), but poor choices of capacity and free-flow speeds can significantly reduce the accuracy of the speeds estimated using this procedure. Note that the consistency of defaults across facilities in a study area, within the same area type (e.g. urban and rural) should be considered. 2. COMPUTATIONAL TOOLS Planning analyses of multimodal transportation systems in large areas are best performed in a travel demand modeling environment which can equilibrate the forecasted demands between facilities and modes based on the forecasted performance. The guidance provided here is on the use of HCM procedures to generate the key performance analysis inputs required by typical demand models. These procedures are generally performed manually with spreadsheet assistance to facilitate and document the calculations. 3. DATA NEEDS Exhibit 112 lists the required input for the analysis of areawide systems of facilities. Individual performance measures may require only a subset of these inputs. 204

205 Exhibit 112. Required Roadway Segment Data for Area and Roadway Systems Analysis Required to Estimate Input Data (units) FFS Cap Spd Que Rel Comments/Defaults Facility Type Defaults by area and facility type Segment design geometry Defaults by area and facility type Terrain type Must be provided Percent heavy vehicles (%) 10% (rural), 5% (urban) Peak hour factor (decimal) 0.88 (rural), 0.95 (urban) Driver pop factor (decimal) 1.00 Number of directional lanes Must be provided Segment length (mi) Must be provided Directional demand (veh/h) Output of Travel Model Notes: See appropriate sections in text for definitions of the required input data. - FFS = free-flow speed - Cap = Capacity (veh/hr/ln) - Spd = Speed (mi/h) - Que = Queue (veh) - Rel = Travel Time Reliability - Facility Type = freeway, arterial by control type (signal, roundabout, etc), multilane or two-lane rural highway. - Segment Design Geometry = varies by facility type but often includes average lane widths, shoulder widths, access point density, etcetera. - Terrain Type = level (short grades < 2%), rolling, mountainous (long grades >4%). See Chapter 9 HCM 2010 for more precise definitions. - Driver Pop Factor = driver population factor used to reduce capacities due to unfamiliar drivers. 4. ESTIMATION OF DEMAND MODEL INPUTS The HCM can support the estimation of two key demand model inputs related to the highway network: the free-flow speed of a link and its capacity. Free-Flow Speed Estimation The free-flow speed of a facility is defined as the space mean speed of traffic when volumes are so light that they have negligible effect on speed. Free-flow speed excludes intersection control delay. The best technique for estimating free-flow speed is to measure it in the field under light traffic conditions, but this is not a feasible option when several thousand streets links must be analyzed. The next best technique is to use the procedures defined in the Highway Capacity Manual. Locally developed look-up tables by facility type and area type may be used to automate the process. Freeway Subsystem The free-flow speeds for all freeway subsystem links (weaving, merge, diverge, and basic segments) can be measured in the field or estimated using the procedures described in Chapter 11, Basic Freeway Segments, of the 2010 HCM (see equation 11-1 HCM 2010). The procedures require information on lane 205

206 widths, lateral clearances, number of lanes, and interchange spacing. Default values for missing data can be found in Chapter 26, Freeway Concepts, and in Chapter 11 of the 2010 HCM. Rural Highway Subsystem The free-flow speeds for two-lane and multi-lane highway links can be measured in the field or estimated using the procedures described in Chapter 15, Two-Lane Highways, and Chapter 14, Multilane Highways of the 2010 HCM. The procedures require information on lane widths, lateral clearances, number of lanes, median type, and access point density. Default values for missing data can be found in those chapters. Arterial/Collector Urban Street Subsystem The free-flow speed for arterial and collector streets can be measured in the field, or estimated using the procedures described in Chapter 17, Urban Street Segments of the 2010 HCM. Default values for this estimation are provided in the chapter. Note that the HCM also defines a base free-flow speed which must be converted to free-flow speed (see equation 17-4 in HCM 2010) before it can be used in planning analyses. Creating a Lookup Table of Free-Flow Speed Defaults The analyst may wish to develop a look-up table of free-flow speeds based upon local surveys and the functional class and the area type in which a link is located in order to simplify the estimation of free flow speeds. Depending upon local conditions, the analyst may wish to classify links by area type (e.g. downtown, urban suburban, rural), terrain type (e.g. level, rolling, mountainous) and frontage development types (commercial, residential, undeveloped) (see representative example in Exhibit 113). The accuracy of the speed estimation procedure is highly dependent on the accuracy of the free-flow speed and capacity used in the computations. Great care should be taken in the creation of local look-up tables so that they accurately reflect the free-flow speeds present in the locality. 206

207 Exhibit 113: Illustrative Look-Up Table of Free-Flow Speed Defaults Facility Type Area Type Default Free-Flow Speed (mi/h) Downtown 55 Freeway Urban 60 Suburban 65 Rural 70 Downtown 25 Arterial Urban 35 Suburban 45 Rural 55 Downtown 25 Collector Urban 30 Suburban 35 Rural 40 Note: facility types, area types and default speed values are illustrative. Other categories and values may be more appropriate for a particular study area. Capacity Estimation Unlike travel demand models, where a roadway link represents all intersections and segments within that specified length of roadway, the HCM deals with segments (between intersections) and intersections separately, before combining them into a facility analysis. The discussion below therefore combines the separate HCM segment and intersection procedures for estimating capacity into a single mini-facility approach able to accommodate the combined effects of segment and intersection capacity on the total link capacity. Generally, the capacity of the link will be determined for demand modeling purposes by the intersection or segment with the lowest through capacity within that link. Options for Estimating Link Capacity: - The best technique for estimating capacity is to measure it in the field at the bottleneck. This is not often feasible, so the next best technique is to employ the procedures contained in HCM. - The HCM capacities, computed in terms of passenger cars per hour (PC Capacity), however, must be converted to mixed vehicle capacities. This must be done to allow the use of actual vehicular demand values in the queuing and delay calculation steps (rather than passenger car equivalents, PCEs). The conversion is done by applying the demand adjustment factors recommended in the HCM to the PC Capacity. The following equations for freeways, multilane highways, two lane rural roads, and arterials illustrate the application of the demand adjustment factors to the PC Capacity. 207

208 Freeway Subsystem The following equation is used to compute the mixed vehicle capacity of a freeway link at its critical point. The critical point is the point on the link with the lowest throughput capacity. c = PCCap x N x F hv x F p x CAF x PHF Equation 181 where: c = capacity (veh/h) PCCap = The HCM passenger car capacity from Exhibit 114 (pc/h/ln). N = Number of through lanes. Ignore auxiliary and exit only lanes. F hv = Heavy vehicle adjustment factor. F p = Driver population adjustment factor. CAF = Capacity adjustment factor to account for weaving, merging, diverging and other effects. PHF = Peak hour factor. Adapted from equation 11-2, 2010 HCM to yield capacity adjustment rather than volume adjustment For freeways use the following HCM PC capacities for basic and ramp merge/diverge sections. The HCM PC capacity basic freeway segments should be reduced 10% for weaving sections. Exhibit 114: HCM PC Capacities for Freeways Free Flow Speed (mi/h) HCM PC Capacity (pc/h/ln) Source: Exhibit 11-2, HCM 2010 See Chapter 11, Basic Freeway Segments, of HCM 2010 for procedures for determining the adjustment factors. See Exhibit of HCM 2010 for suggested default values for the adjustment factors. Rural Multilane Highways The same equation (shown above for freeways) is used to compute the mixed vehicle capacity of a multilane highway (with signals, if any, spaced more than 2 mi apart). Different HCM PC Capacities are used for multi-lane highways and the adjustment factors may take on different values. The HCM PC Capacities shown in Exhibit 115 are used for multi-lane highways. See Chapter 14, Multilane Highways, for the adjustment factor values. Default values for the adjustment factors must be determined locally. Chapter 26 of the HCM 2010 provides data on percent heavy vehicles by state of the US. NCHRP Report #599 6 should be consulted for default values. 6 Zegeer, John, et al., NCHRP Report 599, Default Values for Highway Capacity and Level of Service Analyses, Transportation Research Board, Washington, DC,

209 Exhibit 115: HCM PC Capacities for Rural Multi-lane Highways Free Flow Speed (mi/h) HCM PC Capacity (pc/h/ln) Source: Exhibit 14-2 HCM 2010 Rural Two-Lane Highways and Roads The following equation is used to compute the mixed vehicle capacity (in one direction) for a two-lane road (one lane each direction) with signals (or any other intersection control like all-way stops or roundabouts that slow down through movements) more than 2 miles apart: c = PCCap x F g x F hv x PHF Equation 182 where: c = capacity (veh/h) PCCap = HCM PC Capacity: use 1600 for single direction (pc/h/ln) F g = Grade adjustment factor. F hv = Heavy vehicle adjustment factor. PHF = Peak hour factor Adapted from Equation 15-3 of HCM 2010 See Chapter 15, Two-Lane Highways, for the adjustment factor values. Default values for the adjustment factors must be determined locally. The HCM 2010 does not provide default values for these adjustment factors. The Part 2, Mid-Level Analysis chapters of this Guide or NCHRP Report #599 7 should be consulted for default values. Urban Arterial and Collector Streets The capacity of an urban arterial or collector street link 8 with multiple choke points (signals, all-way stops, lane drops, roundabouts, etc.) is determined by examining the through movement capacity at each choke point on the arterial link. The choke point with the lowest through capacity determines the overall capacity of the arterial link. The following equation is used to compute the one direction through capacity for a signal. 7 Zegeer, John, et al., NCHRP Report 599, Default Values for Highway Capacity and Level of Service Analyses, Transportation Research Board, Washington, DC, The term link, commonly used in demand modeling, refers to a collection of road segments and intersections that are together represented in the model by a single free-flow speed and capacity, and for which the demand model produces a single estimate of demand and average speed. 209

210 c = S o x N x f w x f hv x F g x f p x f bb x f a x f LU x f LT x f RT x F Lpb x f Rpb x PHF x (g/c) Equation 183 where: c = capacity (veh/h) PHF = Peak hour factor. g/c Ratio of effective green time per cycle. s o = base saturation flow rate (pc/h/ln), for metropolitan areas 250,000 population or greater otherwise f w = adjustment factor for lane width, f HV = adjustment factor for heavy vehicles in traffic stream, f g = adjustment factor for approach grade, f p = adjustment factor for existence of a parking lane and parking activity adjacent to lane group, f bb = adjustment factor for blocking effect of local buses that stop within intersection area, f a = adjustment factor for area type, f LU = adjustment factor for lane utilization, f LT = adjustment factor for left turn vehicle presence in a lane group, f RT = adjustment factor for right turn vehicle presence in a lane group, f Lpb = pedestrian adjustment factor for left turn groups, and f Rpb = pedestrian bicycle adjustment factor for right turn groups. - Source: eqn 18-5, 2010 HCM, adapted to include PHF and g/c. See Chapter 18, Signalized Intersections, of HCM 2010 for the adjustment factor values. Suggested default values for the inputs needed to compute the saturation flow adjustment factors are provided in Exhibit of the HCM NCHRP Report #599 9 provides additional default values. For arterials with all-way stops or roundabouts controlling the link capacity the HCM 2010 Chapter 20 and 21 procedures should be used to estimate the through movement capacity at each intersection. Capacity Look-Up Table The accuracy of the speed estimates produced by a demand model are highly dependent on the accuracy of the estimated capacity for the facility. Consequently it is recommended that the analyst use capacities that are specific to each link whenever possible. However it is recognized that this link specific approach is not feasible when evaluating thousands of links in a metropolitan area. The analyst may select sets of default values for the various capacity adjustment factors that vary by functional class (freeway, highway, arterial, collector, local), area type (downtown, urban, suburban, rural), terrain type (level, rolling, mountainous) and other conditions. These default values may be substituted into the above capacity equations to develop a set of look-up tables of link capacities that vary by functional class, area type, general terrain, and number of lanes. 9 Zegeer, John, et al., NCHRP Report 599, Default Values for Highway Capacity and Level of Service Analyses, Transportation Research Board, Washington, DC,

211 The effects of the heavy vehicle, constrained geometry, peaking, and other factors are generally to reduce the base capacity (which is expressed in terms of PCEs per hour per lane) by between 10% and 20%. The 10% reduction is typical of facilities meeting agency design standards on level terrain carrying modest numbers of heavy vehicles (5% or less), with typical peak hour factors in the range of 92% to 97%. The 20% reduction is typical of facilities with various geometric constraints, higher heavy vehicle use, and/or higher peaking characteristics (which results in lower peak hour factors). The saturation flow rates for signalized arterials must be first discounted by the g/c ratio (percent green time) for the through lanes on the arterial. Research in Florida (see FDOT Q/LOS Handbook 10 ) suggests that g/c s of 41% are a practical maximum for suburban arterials with left turn phases and typical left turn volumes at major intersections. Higher values may be achieved for the mainline through lanes at intersections without left turn phases, on one-way streets, and at intersections of major streets with a minor cross street. Other values can be (and should be) selected based on local experience. Exhibit 116 illustrates the construction of a capacity per lane look up table from which the analyst can select capacity values from the 90% and 80% PC Capacity columns depending on the analyst s general assessment of facility conditions. Unique situations may also warrant greater capacity reductions than shown in this illustrative table Quality/Level of Service Handbook, Florida DOT, Tallahassee, FL,

212 Exhibit 116: Illustrative Capacity Per Lane Look-Up Table Facility Type Freeway Arterial Collector Notes: Area Type Free-Flow Speed (mph) G/C HCM PC Capacity (pc/ln) 90% HCM PC Capacity (veh/ln) 80% HCM PC Capacity (veh/ln) Downtown 55 n/a Urban 60 n/a Suburban 65 n/a Rural 70 n/a Downtown Urban Suburban Rural Multi-Lane 55 n/a Rural 2-Lane 55 n/a Downtown Urban Suburban Rural Multi-Lane 45 n/a Rural 2-Lane 45 n/a PC = passenger car equivalent capacity. - Categories and values are illustrative. Other categories and values may be more appropriate. - Table prepared for metropolitan area with population of 250,000 or greater. - HCM PC Capacity includes g/c effects, if appropriate. - The 90% PC capacity column is used where the effects on capacity of heavy vehicles, peaking, and substandard geometry (if any) are expected to be negligible to minor. - The 80% PC capacity column is used where substandard geometry, grades, heavy vehicles and peaking are expected to have greater impacts on capacity. 212

213 5. PERFORMANCE MEASURE ESTIMATION Performance measure estimation is accomplished mostly within the travel demand model environment. This section focuses on the use of HCM procedures to estimate the roadway related performance plus two performance measures not typically produced by travel demand models: queuing and reliability. The discussion is split between the estimation of auto related performance measures, and multimodal performance measures (truck, transit, bicycle, and pedestrian). Auto Related Performance Measures Demand-to-Capacity Ratio The demand to capacity ratio for each link is typically output by the travel demand model, based on the analyst input capacity. Average Travel Speed and Average Travel Time The mean vehicle speed for through trips on a link is computed by the travel demand model during an traffic assignment process using either a speed-flow equation or a more sophisticate approach that combines link delay with an estimate of node delay. Demand Models That Compute Node Delay If node delay is used by the demand model, then the following equation is used to compute average link speed including node delay. S L R D Equation where: S = mean link speed (mi/h), L = link length (mi), R = link travel time (h), D = node delay for link (s). The node delay (D) is computed only for the signal or stop sign control intersection located at the end of the link (all other intersection related delays that occur in the middle of the link are incorporated in the link travel time calculation). The node delay procedures described later for Interrupted flow facilities. The calculation requires information on all of the intersection approaches at the node in order to compute the mean approach delay for each link feeding the intersection. Demand Models that Do Not Compute Node Delay If the available travel demand model software package is unable to compute node delay, the delay can be approximated by using the node approach capacity rather than the link capacity in the computation 213

214 of travel time (T). In this situation the node delay is set to zero in the above equation for predicting link speed. Note also that for models that do not separately model node delay, it is necessary to include the intersection control delay at zero volumes in the estimated free-flow speed for each link. This diverges from the HCM practice of excluding intersection control delay from the free-flow speed for urban streets. The standard speed-flow equation used in conventional equilibrium traffic assignment processes is the Bureau of Public Roads equation. An alternative that has been presented in this Guide is the Akcelik equation. The analyst may select between these two as well other speed-flow equation forms. This step focuses on how the Akcelik equation produces speed-flow estimates that better match deterministic queueing analysis employing HCM methods. Bureau of Public Roads Equation T T * 1 0 Akcelik Equation B Ax Equation III-185 T 0.25H 16J L H 2 2 T0 x 1 x 1 2 x Equation III-186 Where: T = link travel time (h), T 0 = link travel time at low or near zero volumes (h), A = ratio of speed at capacity to free-flow speed, minus one. (std value = 0.15) B = BPR parameter that affects the rate at which the speed drops (standard value = 4.0). H = the expected duration of the demand (typically one hour) (h); x = the link demand/capacity ratio; L= the link length (mi). J = the calibration parameter. S = mean speed (mi/h) S f = free-flow Speed The calibration parameter J for Akcelik and the A parameter for BPR are selected so that the travel time equation will predict the mean speed of traffic when demand is equal to capacity. 214

215 Substituting X=1.00 in the BPR travel time equation and solving for A yields: A = S f S c 1 Equation 187 Substituting X=1.00 in the Akcelik travel time equation and solving for J yields: J 1 1 S c S f 2 Equation 188 Where: A = BPR speed at capacity calibration parameter J = Akcelik Parameter S c = mean speed at capacity (mi/h) S f = mean free-flow speed (mi/h) Exhibit 117 shows the recommended capacities, speeds at capacity, values for J that were selected to reproduce the travel times at capacity predicted by the analysis procedures contained in 2010 HCM. 215

216 Exhibit 117: Recommended Speed Flow Equation Parameters Facility Type Freeway Principal Highway Minor Highway Arterial Collector Area Type Free-Flow Speed (mi/h) Capacity (veh/ln) HCM Base Speed at Capacity (mi/h) BPR a Parameter Akcelik J Parameter Downtown** E-06 Urban E-06 Suburban E-05 Rural E-05 Rural Multi-Lane E-06 Rural Two-Lane E-06 Rural Multi-Lane E-06 Rural Two-Lane E-05 Downtown ** E-06 Urban E-06 Suburban E-06 Downtown E-06 Urban E-05 Suburban E-06 *The speeds and capacities shown here for downtown freeways may not be appropriate for more modern central business district and downtown areas. **These values highlighted in yellow need to be revisited. The speeds at capacity are too high. R.Dowling. Selecting a Speed-Flow Equation As illustrated in the example queuing diagram shown in Exhibit 118, when demand exceeds capacity, the simple physics of a bottleneck dictates that delay should increase linearly for d/c s greater than The BPR equation increases delay exponentially, not linearly. The Akcelik equation increases delay linearly (see Exhibit 119). Exhibit 119 confirms the linearity of delay for demands greater than capacity through an example application of the HCM 2010 operational analyses of a 9.3 mile long freeway in Florida. The Akcelik curve does not start discounting uncongested speeds until approaching 90% of capacity. However, in this range of d/c ratios shown here, the speed differences result in negligible differences in predicted travel times. At the highest d/c ratio tested, the HCM 2010 analysis tool is showing limitations in its ability to properly account for exceptionally long queues. 216

217 Exhibit 118: Example Queuing Diagram Exhibit 119: Speed-Flow Equations Versus HCM 2010 Travel Time Results for Freeway 217

218 Exhibit 120 is a more traditional plot of speed versus demand. The BPR curve to the power of 4 fits the HCM data best for d/c s below 1.0, but for values in excess of that the BPR curve to the power of 4 greatly overestimates speeds for congested conditions. The BPR curve to the power of 10 and the Akcelik curve perform similarly for d/c s less than 1.20, with both curves slightly overestimating speeds for d/c s less than 1.00 and matching the HCM estimated speeds for d/c s between 1.00 and The two curves diverge for d/c s greater than 1.20 with the Akcelik curve continuing to follow the HCM analysis, and the BPR curve to the power of 10 greatly underestimating speeds. Exhibit 120: Example fit of Speed-Flow Equations to HCM 2010 Speed-Flow Results for Freeway An additional consideration in the selection of the speed-flow equation for demand modeling purposes is how each equation reacts to short links. The Akcelik equation adds the queue delay to the free-flow travel time of the link. The BPR factors the free-flow travel time for the link according to how greatly the predicted demand exceeds capacity. The BPR s factoring approach treats the link as a rough pipe with congestion slowing down traffic the entire length of the pipe. Akcelik s additive approach treats the link as a smooth pipe with a funnel at its entrance to temporarily store excess demand until it can flow through the pipe (see Exhibit 121). 218

219 Exhibit 121: The Smooth and Rough Pipe Analogy for Speed Flow Equations The BPR s factoring approach works best for demand model assignment routines using static equilibrium assignment methods that allow the model to assign demands greater than capacity throughout the network. In this situation, all generated demand is assumed to reach its destination in the analysis period. Thus, links downstream of a bottleneck are also assigned demands greater than the capacity of the bottleneck. In essence, delays due to bottlenecks are double counted downstream of the bottleneck, but because the BPR proportions the delay according to the length of the link, the effect of the double counting is not as severe as when the Akcelik equation is used. A bottleneck link can be divided in two sublinks and the BPR predicted travel time for the two sublinks will still sum to the travel time for the original bottleneck link. The Akcelik curve treats each link as having a strict physical capacity that cannot be violated. Every vehicle entering the link must wait its turn, accumulating delay, until it can pass through the link. This delay is independent of the length of the link, so dividing a bottleneck link in two results in doubling the delay estimated by Akcelik, since each link is treated as its own bottleneck with its own waiting line. This Akcelik approach of additive delays works less well in static equilibrium assignments where demands are not constrained downstream of a bottleneck. The Akcelik equation is less forgiving of over assigning demands downstream of a bottleneck. However, the Akcelik additive approach would work better than the BPR approach when used in a dynamic traffic assignment (DTA) model where demand is sequentially loaded on the network and stored in the network at the bottlenecks (which matches the Akcelik assumption of a funnel leading to each link). Thus the choice of speed-flow equation to use depends on the model within which it will be used. For models using static equilibrium assignment, a version of the BPR equation may work best for predicting system travel times, but not the travel times for specific links in the network. A dynamic traffic 219

220 assignment will yield more accurate estimates of link specific speeds, especially when the Akcelik equation is used. Vehicle Hours and Person-Hours of Delay Vehicle-hours and person-hours of delay are typically output by the travel demand model using thresholds specified by the analyst. Vehicle-hours and person-hours of travel time may be compared an agency specified minimum speed goal for each link. The speed goal may be the link free-flow speed, or some other value. Level of Service The HCM provides level of service measures for road segments, freeway segments, and intersections. Level of service measures are also provided for freeway facilities and urban street facilities, but they are applicable to only those individual facility types, and begin to lose their meaning (masking out problem spots within the facility) when applied to facilities over 10 miles in length. Aggregate performance measures, such as vehicle-miles (or person-miles) traveled (VMT or PMT), vehicle-hours (or person-miles) traveled (VHT or PMT), and vehicle-hours (or person-hours) of delay (VHD, or PHD) are generally the best basis for comparing future system performance to existing conditions or to future investment alternatives. However, it is often difficult to convey the significance or meaning of numerical results to the general public or decision-makers. Analysts may use level of service (LOS) letter grades (A-F) to try and convey the degree of acceptability of the performance results, however; one should use care when simplifying numerical results to a few letter grades. Rather than reporting a single letter grade for the entire system or mode of travel, areawide or systemwide LOS reports should report the distribution of the segment and intersection LOS results, weighted by the VHT (vehicle-hours traveled) experiencing each specific segment and intersection LOS. The link 11 LOS is computed from travel demand model link output by facility type and intersection control type. Service volume tables may be used to estimate link LOS. The analyst may then choose to report the percentage of daily VHT experiencing each LOS grade by mode within the system. Further value can be gained by breaking down the road system results by facility type and area type. Exhibit 122 shows an illustrative system LOS report. Exhibit 123 shows how the system report for non-freeway facilities might be displayed in a dashboard format. 11 The term link, a term common in demand modeling, is used in this discussion to represent a combination of HCM segments and intersection controls for which the demand model assumes a single free-flow speed and a single capacity, and for which the model outputs a single forecasted demand and estimated speed. 220

221 Exhibit 122: Illustrative System LOS Report Typical Weekday Peak Period Area Type Facility Type Mode LOS A-C LOS D LOS E LOS F Total Freeways Auto 7% 24% 38% 31% 100% Truck 4% 20% 38% 38% 100% Auto 16% 34% 34% 16% 100% Urban Truck 5% 22% 38% 34% 100% Non-Freeway Transit 10% 29% 38% 24% 100% Bicycle 12% 31% 37% 21% 100% Pedestrian 31% 38% 24% 7% 100% Values and categories are illustrative. Other area types, facility types, and modes may be appropriate. Exhibit 123. Illustrative System LOS Dashboard Typical Weekday Peak Period Values and categories are illustrative. Other formats and modes may be appropriate. Note that, at this point, the focus is on the results for a single average weekday with fair weather and no incidents, such as is typically produced by a travel demand model analysis. The reliability of that result under varying incident and weather conditions over the course of the year is addressed by postprocessing the single day results produced by the model, as later described in the reliability analysis discussion of this chapter. Auto Service Volume Tables Auto service volume tables are specific to the facility type. See the appropriate chapter for facility specific service volume tables. Density Density can be computed for each roadway link by dividing the demand model predicted direction volume in vehicles per hour per through lane by the demand model predicted average link speed in miles per hour. The result is average density of vehicles per through lane per hour per mile. Queuing This section describes a procedure for estimating total system vehicle-hours in queue. The predicted demand for the link is multiplied by the average travel time for the link to obtain the vehicle-hours traveled (VHT). 221