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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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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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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Synchro Model Emme Model

Dynameq Network

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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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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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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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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


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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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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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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


2011 Calibration Statistics – AM Peak Hour

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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


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2014 Travel Time Comparison

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2014 Simulated Speed Difference (5:30 – 6:30 AM)

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Modelling Process: Model Analysis

Traffic Volumes and Travel Speeds

Performance Metrics

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Travel Times Queue Lengths


Performance Metrics

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Link-Based Time Series Lane-Based Time Series


Performance Metrics

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Movement-Based Time Series Turn-Based Time Series


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

Meso-scopic Traffic Modelling in Greater VancouverMeso-scopic Modelling Realistic modelling of...

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