INCORPORATING CYCLING IN OTTAWA-GATINEAU TRAVEL MODEL Surabhi Gupta & Peter Vovsha, Parsons Brinckerhoff Inc. Ahmad Subhani, City of Ottawa
Ottawa-Gatineau Region National Capital Region Fourth Largest Urban area in Canada (1.2 million population; 670K jobs) Ottawa region is 2,796 square kms (1,800 square miles) On the banks of the Ottawa, Rideau, and Gatineau rivers Transportation System Good Network of Highways Transit Options Local Buses, Express Buses, O-Train Transitway (BRT) LRT (under development) Other Modes Spring/Summer/Fall Bicycling Winter Skating on the Canal
Why Cycling? Strong growth in cycling observed between 2005 and 2011 Regional bicycling share 2005 2011 Daily 1.25% 1.75% Peak Periods 1.5% 2.5% Targets for Cycling in Ottawa
Promoting Bike-and-Ride Focusing on Cycling Networks around Transit Oriented Development Zones Providing ample parking at Transit Stations 4
Existing Model Java based population synthesizer Daily tour-based structure for travel generation and spatial distribution EMME based Limited segmentation (HH variables) Conventional trip-based mode choice and traffic/transit simulations for AM and PM
Objective Bike as an additional mode in mode choice model Detailed bike routing/assignment based on LOS measures with cross-impacts of auto traffic and bike movements Develop LOS measures for bicycles that include link and node-level factors Consider effect of perceived bike LOS measures on mode choice
Variables affecting Bike LOS & route choice Variables Link-Level Traffic Stress (Mineta) BLOS (Landis et al) BCI (FHWA-RD- 98-095) BLOS (NCHRP- 616) Model SFCTA Model BLOS (Dixon) League of IL Bicyclists Bike Route Preferences (Stinson and Bhat) Vehicle Flow Rate Y Y Y EN Number of Through Lanes Y Y Y EX Speed Y Y Y Y Y Y EX % Heavy Vehicles Y Y Y Y EN Pavement Condition Y Y Y Y EX Lane Width Y Y Y Y EX Shoulder (yes/no) Y Y Y Y EX Parking (Yes/No) Y Y Y Y Y EX Parking Width Y Y Y EX Bike Lane Blockage (Yes/no) Y Y EX Bike Facility /Lane/Shoulder Y Y Y Y Y EX Bike Lane Width Y Y EX Shoulder Width Y Y Y EX Type of Road: Residential, Arterial etc Y Y Y EX Trip Generation Intensity Y EN Driveways (Yes/No) Y EX Unrestricted Sight Distance Y EX Terrain (Flat, Hilly, Mountainous) Y EX AADT Y Y EX Median (Yes/No) Y EX Curb Lane Width Y Y Y EX Node/Turn Level Type Signal (Yes/No) Y EX Right Turn Lane (Yes/No) Y Y Y EX Left Turn Lane (Yes/No) EX Right Turn Pocket Lane (Yes/No) Y EX Cross Street Width Y EX Turn Movements EX Right Turn Lane Length Y EX Left Turn Lane Length EX NY State BCI Type
Summary of State of Practice Large number of qualitative studies First attempts to incorporate bike in mode choice (San Francisco, Portland, LA) No examples yet of bicycle network assignment
Bicycle LOS and Volume-Delay Function LOS can be segmented based on User class and Bike facility type Types of Users Classification A (Mineta Report, Dill et al., Geller) Strong, Enthusiastic and Interested Example splits in Portland (Dill et al.): 4% Strong, 9% Enthusiastic, 56% Interested, 31% Never Classification B (Bhat et al.) Experienced and Inexperienced Types of Bike Facilities - Grade Separated, Exclusive Lane, Mixed-Traffic
Bicycle LOS and Volume-Delay Function Bicycle travel time affected by: Auto volume high V/C ratio for autos implies a steeper bicycle VDF as they have to navigate through high congestion for mixedtraffic Bicyclist type Stronger/experienced bicyclists have higher free flow time and lower sensitivity to congestion and auto traffic Bike lane type Easier to navigate through dedicated bike lane than mixed traffic Total effective capacity effective capacity available to bikes conditional on the modeled traffic volumes
Bicycling Facility Types in Ottawa Region Multi-use Stone pathway and Asphalt pathways (shared by pedestrians and bicyclists)
Bicycling Facility Types in Ottawa Region Exclusive Bike Lanes (physically separated or marked)
Bicycling Facility Types in Ottawa Region Sharrow Lanes Bikes allowed in mixed traffic Paved Shoulders
Bike Travel Time Function (VDF) Bike link travel time (VDF) t( Vb) = Bike Free Flow Time Link Delay Factor (LDF) Auto Congestion Factor (ACF) Congestion effect due to other Bicycles Cycling Conditions Reduced Speed due to Auto Congestion tb
Link Delay Factor (LDF) Delay (travel time) experienced by the bicyclist: Link Delay ijm = LDF ijm Bike Free Flow Time Where, the link delay factor (LDF) is defined as: i, j A m M Link Delay Factor (LDF) LDF ijm = 1 + LOS ijm i, j A m M In turn, LOS ijm is defined as: LOS ijm = Max f A ij, P i, P j, M m A ij, 0 Where: 1+LOS A ij = Link specific variables, P i = Downstream node-specific variables, P j = Upstream node-specific variables, M m A ij = Link-user specific interaction variables.
Link Delay Factor (LDF)- Example Network Attribute Bicyclist Variables Multiplier Units Value [A] Effect [B] [A] x [B] Link-Level Bicycle Lane (yes/no) N/A 0 Decrease -1.12 0 Sharrow Lanes N/A 1 Decrease -0.5-0.5 Bike Lane Width Feet 5 Decrease -0.4-2 Curb Lane Width Feet 10 Decrease -0.0498-0.498 Traffic Speed kph 35 Increase 0.01375 0.481 Curb Lane Volume Vph 600 Not Good 0.002 1.2 Other Lane Volume Vph 1200 Not Good 0.0004 0.48 Parking Lane (yes/no) N/A 1 Increase 0.506 0.506 % Heavy Vehicle Volume Ratio 15 Increase 0.034 0.51 Frequency of driveways N/A 3 Increase 0.019 0.057 Pavement Condition (good/bad) 0-4 0 Increase 0.05 0 Node-Level Signal N/A 1 Increase 0.011 0.011 LOS 0.23625 Free Flow Travel Time (FFTIME) mins 6 Delayed Travel Time (FFTIME x (1+LOS) mins 7.48
Auto Congestion Factor (ACF) Reduction in Bike Speed due to Auto congestion: Auto Congestion Factor (ACF) Only affects the bicycles in mixed traffic For bicycle lanes and multi-use pathways, ACF = 1.0 Reduced Speed due to Auto Congestion
Travel Time (Mins) Link Volume Delay Function (Bicycle) Bike VDF is given by: Parameters 35 α β γ θ μ ν δ LDF 5000 6 0.1 4 1 1 0.5 4 0.1 1.2 High Auto V/C t V b = t b 1 + δ b V b C eff Exp eff 30 Congestion effect due to other Bicycles 25 20 Medium Auto V/C 15 10 Low Auto V/C 5 0 0 1000 2000 3000 4000 5000 6000 Bike Volume
Travel Time (mins) Link Volume Delay Function (Auto) Impact of bicycles on auto travel times Presence of bicycles increase auto travel times Bicycles take up capacity, and since they move slower than autos, they take up more capacity than their physical dimensions The reduction in capacity due to bicycles accounts for these impacts 5.5 5 4.5 Parameters ζ β 5000 3 0.1 3 1 1.33 PCE 0.8 Bikes in Mixed- Traffic High Bike Volume Medium Bike Volume Low Bike Volume 4 Dedicated Bike Lane High Bike Volume 3.5 Medium Bike Volume Low Bike Volume 3 0 1000 2000 3000 4000 5000 Auto Volume
Iterative Auto-Bicycle Assignment
Modeled Bike Flow Map: AM Peak Hour
Model Validation 300 Protage Bridge 200 Alexandre Bridge 200 100 100 0 Southbound Northbound 0 Southbound Northbound Count Volume Count Volume 400 Laurier at Metcalfe 150 100 Colonel By Dr 200 0 Westbound Count Eastbound Volume 50 0 Southbound Count Northbound Volume
Future Improvements: Turn Penalties f k V a, V b, k f k V a, V b, f k V a, V b, k k j i For turn i-j-k: t V a = TP a ijk + t 0 LF 1 + ζ a V a + p bl b C V b β a k k t V b = TP b ijk + ACF 1 + ζ b V b C eff Exp eff k j Turn i j k i
QUESTIONS!