An Investigation of Freeway Capacity Before and During Incidents

Transcription

1 An Investigation of Freeway Capacity Before and During Incidents Cuie Lu and Lily Elefteriadou Department of Civil and Coastal Engineering University of Florida March 4, 2011

2 Outline Database and Analysis Procedure Capacity for Normal (i.e., Non-incident) Conditions Capacity for Incident Conditions

3 l. Incidents on freeway may block one or more lanes and/or the adjacent shoulder lane: What is the capacity for incident conditions? What other factors affect capacity? Incident management, queue estimation Capacity-Normal

4 Federal Highway Administration (FHWA) : An incident blocking one lane out of three on a freeway reduces the capacity by about 50% Blocking two lanes of three reduces capacity by nearly 80% Capacity-Normal

5 The capacity remaining after an incident is estimated based on the number of lanes blocked by the incident. However, - doesn t consider other factors such as incident category and geometric characteristics - no models relating the capacity before an incident to the capacity after an incident Capacity-Normal

6 The objectives are to: Assess freeway capacity under normal (i.e., no incident) conditions Compare capacity remaining after incidents to previous research Develop models to predict incident capacity and capacity reduction Capacity-Normal

7 II. Database and Analysis procedure A subset of data collected for the NCHRP 3-87 project (Elefteriadou et al., 2009) Site Location Length (mi) Data Period Traffic Data * Weather Data Incident Duration Number of Lanes Closed/ Affected I-15 SB San Diego, CA / /2007 V, O Y Y N I-5 NB Sacramento, CA / /2007 V, O Y Y N QEW Toronto, Canada / /2005 V, O, S Y N Y I-494 SB Minneapolis, MN 3 09/ /2007 V, O, S Y Y Y OR 217 SB Portland, OR 7 01/ / / / / /2008 V, O, S Y Y Y * V- Volume, O- Occupancy, S-Speed

8 Data Analysis Procedure a. Data Screening and Incident Categorization Remove adverse weather and missing or erroneous observations Incident verification: by speed and occupancy time series plots Incidents categorization: - incidents occurring before congestion - incidents occurring during congestion - incidents occurring downstream

9 Data Analysis Procedure b. Breakdown Identification: speed drop of more than 10 mph, three criteria (Elefteriadou et al., 2009): S i Avg S i S i 1 0 Si 5,..., Si 1 Avg Si,..., Si 4 10mph Max S i,..., Si 9 Si 1 Defines recurrent congestion as demand-induced breakdown, congestion caused by incidents as incidentinduced breakdown

10 III. Capacity under Normal Conditions A. Breakdown flow; B. Maximum pre-breakdown flow C. Ave. flow for 10 minutes before breakdown; D. Average discharge flow Capacity- Normal

11 Capacity parameters by vs. number of lanes breakdown flow lanes (# 80 data points) 3 lanes (105 data points) 4 lanes (79 data points) 5 lanes (34 data points) max.flow 10 min before breakdown ave. flow 10 min before breakdown ave. discharge flow Capacity- Normal

12 As shown in the Figure: Three-lane freeways is more productive in terms of per lane capacity - might due to lane-changing behavior Breakdown flow is generally higher than the average discharge flow Breakdown flow has the largest range of values, while average discharge flow the smallest range of values. Capacity- Normal

13 IV. Capacity under Incident Conditions Data: three sites (Minneapolis, Portland, and Toronto), as these provide data on the number of lanes affected Factors: - Incident category (before or during congestion) - Incident location (at bottleneck or non-bottleneck) - total number of lanes - speed limit et al.

14 Incident capacity (two parameters): the average discharge flow per open lane when both incident and congestion are present (in red) the minimum 10- minute flow rate when both incident and congestion are present (in blue) Example: March 9, 2005 (Toronto)

15 Relationship between incident capacity and # lanes affected # Lanes open # Lanes affected # Data points Average flow per total lanes (veh/h/ln) Average flow per open lanes (veh/h/open lane) Minimum 10-min flow rate (veh/h/ln) * 237 shoulder * shoulder Shoulder Note: *assumes there is a passage for the vehicles on the shoulder or between the lanes, or that all lanes are closed only for a brief amount of time.

16 Capacity remaining after incidents (calculated in two ways): as the ratio of the minimum 10-min flow rate to the average discharge flow for normal conditions (averaged for each site) as the ratio of the minimum 10-min flow rate to the 10-min flow before breakdown for normal conditions (averaged for each site)

17 Compare capacity remaining after incidents to previous research: Author Number of lanes Lanes blocked shoulder 1 lane 2 lanes 3 lanes Goolsby, (27 data points) N/A HCM Smith et al., (27 data points) N/A N/A N/A Chin et al., * * * Lu and Elefteriadou, 2011 (average discharge flow) Lanes affected 2 (60 data points) N/A 3 (30 data points) N/A c N/A 2 (60 data points) N/A Lu and Elefteriadou, 2011 (ave. flow 10-min before 3 (30 data points) breakdown) N/A N/A

18 Reasons of differences: Normal capacity: - Previous research: the peak/maximum of the flow-density curve - This research: the ave. discharge flow or ave. flow 10-min before breakdown the number of lanes affected vs the number of lanes blocked by incidents

19 Estimate of the minimum 10-min flow rate: Parameter Description Estimate Error t Value Pr> t Incident category: 1-during congestion before congestion One lane affected <.0001 Two lanes affected <.0001 Shoulder affected <.0001 R-square 0.49 Root MSE

20 Estimates of total capacity reduction: uses average discharge flow as capacity for normal conditions and the minimum 10-min flow as capacity for incident conditions Parameter Description Estimate Error t Value Pr> t Incident category: 1-during congestion 0-before congestion Total number of lanes <.0001 One lane affected Two lanes affected Shoulder affected <.0001 R-square 0.67 Root MSE

21 Total capacity reduction results in a better model: capacity.. reduction 386 inccate 1361 nlane 2008,..shoulder - affected -1172,..1- lane..affected - 77,..2- lanes..affected

22 V. Three-lane freeways seem to be the most efficient in terms of per lane capacity for normal conditions Two incident parameters: the minimum 10-min flow rate provides a better fit with the data reported Three factors significant in incident capacity analysis: - number of lanes affected - incident category - total number of lanes No linear relationship between incident capacity and number of lanes affected

23 Recommendations: Record incident data in more detail on the number of lanes closed More data on: shoulder plus one lane affected shoulder plus two lanes affected

24 My contact information: Cuie Lu Questions and Comments? Thank you!