Meso-scopic Traffic Modelling in Greater VancouverMeso-scopic Modelling Realistic modelling of...
Transcript of Meso-scopic Traffic Modelling in Greater VancouverMeso-scopic Modelling Realistic modelling of...
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Meso-scopic Traffic Modelling in Greater Vancouver
Presented by:
Joanne Ng
M.A.Sc., P.Eng., P.E.
CITE QUAD Conference
May 1 – 2, 2015
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Overview
Meso-scopic Traffic Modelling
Modelling Process
Model Development
Model Calibration
Model Analysis
Challenges
Conclusions
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Meso-scopic Traffic Modelling
Modelling Network Conditions That Result from Mutual Interactions Among Travellers’ Route Choices
Time-Dependent Interactions Between Individual Trips and Network
Dynamic Traffic Assignment (DTA)
Iterative Procedures
User Equilibrium: For Each Origin-Destination Pair, Every Route Used Has Same Travel Time
Efficient Computation Time
Large Geographic Scope
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Meso-scopic Traffic Modelling
INRO Dynameq Software Used
Compatibility with Greater Vancouver Regional Transportation Model (RTM) developed using INRO Emme software
Traffic routing: Dynamic User Equilibrium (DUE)
Simulation-based DTA with car-following, lane-changing, and gap-acceptance models
Value of Time modelled for tolling impacts
Size 5 Licence (1250 zones, 6250 nodes, 20000 links)
Version 2.7.0.5
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Modelling Process
2011 Conditions
Model development
Model calibration
2014 Conditions
Model network updates (major regional network improvements)
Model calibration updates (Fraser River Crossings)
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Modelling Process: Model Development
Model Network Development
Network Initially Developed in Synchro
Buffer Portion Added Subsequently
To allow vehicles to enter core portion via appropriate arterials
Lower level of network details than core portion
Network exported from Regional Transportation Model (Emme)
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Modelling Process: Model Development
Synchro Model Emme Model
Dynameq Network
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Modelling Process: Model Development
Network Data
Lane based
Detailed intersection configurations
Traffic controls
Signal timings
Posted speeds
Transit lines
Time of Day restrictions
Parking
Turning movements
Network
Elements
Number
Traffic Zones 304
Intersections /
Junctions
5,712
Signalized
Intersections
649
Links 13,671
Turning
Movements
33,928
Transit Lines 207
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Modelling Process: Model Development
Demand Data
Hourly Demand from Regional Transportation Model Phase 2 Beta Version (Emme)
24-hour model
Regional Peak Hour
• Morning: 7:30 to 8:30 am
• Afternoon: 4:30 to 5:30 pm
Very coarse zones: 641 traffic zones for Greater Vancouver
12 vehicle classes based on income level and trip purpose
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Modelling Process: Model Development
Meso-scopic Models
Morning Peak Period: 5:30 to 9:30 am
Afternoon Peak Period : 2:30 to 6:30 pm
Vehicle classes aggregated to four (SOV, HOV, Light Trucks, and Heavy Trucks) to reduce computation time
304 traffic zones
Number of trips in Peak Hour: 164,000 trips
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Modelling Process: Model Calibration
2011 Conditions
Local Knowledge
Traffic Volume Data
TransLink’s 2011 Regional Screenline Survey
Turning movement and link counts
Traffic volume balancing
Calibration Process
Initial Demand Adjustments
Network Debugging
Route Choice Analysis
Additional Demand Adjustments
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Modelling Process: Model Calibration
Initial Demand Adjustments
Based on observed counts at model network gates
Fraser River screenline total hourly demand
Fraser River crossings estimated hourly demand
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2011 Fraser River Crossings Estimated Demand
Modelling Process: Model Calibration
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Modelling Process: Model Calibration
Network Debugging
Network Coding Errors
Errors in original Synchro and Emme models
Errors related to Synchro Import feature
Inconsistent attribute definitions between Emme and Dynameq environments
Lack of Modelling Capability for Signal Actuation
Extensive manual signal timing modifications made for Peak Hour conditions
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Modelling Process: Model Calibration
Route Choice Analysis
Parallel Roads in Buffer Attracted Traffic due to Lower Delays
Network details in buffer subsequently brought to same level as core
Coarse Traffic Zones Necessitated:
Use of many zone connectors
Use of turn penalty at connectors to control where traffic is loaded / unloaded within a zone
Many test runs required for turn penalty values
Calibration schedule increased significantly
Calibration Efforts Focused on
Smaller area
Regional Peak Hour
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Modelling Process: Model Calibration
Additional Demand Adjustments
After Network Debugging and Route Choice Analysis Completed
Issues in Regional Transportation Model Beta Version (Emme)
Incorrect travel patterns modelled for residential and industrial zones
Specific origin-destination demand adjustments based on land use and local knowledge
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Link Volume Comparison
Slope = 1.03 R2 = 0.95
Turn Volume Comparison
Slope = 1.06 R2 = 0.91
Modelling Process: Model Calibration
2011 Calibration Statistics – AM Peak Hour
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Modelling Process: Model Calibration
2014 Conditions
Major Regional Road Improvements Completed in Phases in 2012 and 2013
Highway 1 Corridor including new and tolled Port Mann Bridge
South Fraser Perimeter Road Corridor
Additional Calibration Efforts on Fraser River Crossings
Traffic volume data
Estimated demand
Origin-Destination Travel Time Comparison
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2014 Fraser River Crossings Estimated Demand
Modelling Process: Model Calibration
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Modelling Process: Model Calibration
2014 Travel Time Comparison
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Modelling Process: Model Calibration
2014 Simulated Speed Difference (5:30 – 6:30 AM)
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Modelling Process: Model Calibration
2014 Simulated Speed Difference (6:30 – 7:30 AM)
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Modelling Process: Model Calibration
2014 Simulated Speed Difference (7:30 – 8:30 AM)
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Modelling Process: Model Calibration
2014 Simulated Speed Difference (8:30 – 9:30 AM)
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Modelling Process: Model Analysis
Traffic Volumes and Travel Speeds
Performance Metrics
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Travel Times Queue Lengths
Modelling Process: Model Analysis
Performance Metrics
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Link-Based Time Series Lane-Based Time Series
Modelling Process: Model Analysis
Performance Metrics
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Movement-Based Time Series Turn-Based Time Series
Modelling Process: Model Analysis
Performance Metrics
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Challenges: Model Development
Model Network Imported from Other Models
Coding errors within original models imported
Synchro Import feature errors without warnings
Attribute definitions different in Emme and Dynameq
Inconsistent Level of Network Details in Core and Buffer
Resulted in parallel roads in buffer being more desirable due to lower intersection delays
Regional Transportation Model Phase 2 Used While in Beta Version
Pros: Hourly shoulder demand available
Cons: Incorrect assumptions identified resulting in multiple re-runs made and sets of demand generated
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Challenges: Model Calibration
No Subarea Model of Regional Transportation Model Developed
Coarseness of zone system made model calibration very challenging and time-consuming
Long Model Computation Time
Full impacts of changes not available until following day
Lack of Capability for Signal Actuation
Considerable effort on modifying signal timings based on turning movement counts
Software Technical Issues
No warnings for matrix import issues (e.g. missing zones)
Run Multiple DTAs feature unreliable
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Conclusions
Meso-scopic Modelling
Realistic modelling of time-dependent interactions between trips and network
Reasonable traffic congestion and diversion modelled
Lessons Learned
Importance of careful scoping of model spatial limitations
Significance of network details in achieving modelling realism
Refinement of travel demand zone system based on project needs
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Thank You