Manhattan Traffic Model - New York Metropolitan Transportation ...

Manhattan Traffic Model:Technical OverviewNew York City Department of TransportationPresentation to the BPM Users GroupMarch 4, 2010

• 34 th Street Transitwayproject:Manhattan Traffic Model: Why?– “Step-down” from BPM– Dynamic assignment ofsubregional diversions– Integrate findings into EIS– Direct link to operations• Area-wide framework– Basis for future dynamicsimulations– Model cumulative impactsof current/future projects

Manhattan Traffic Model:Key Technical Components• Dynamic traffic assignment– Realistic re-distribution of traffic in the face ofnetwork changes– Complexity of 34 th Street project makes manualadjustment of flows impossible• Integrated mesoscopic and microscopic models– Allows for dynamic assignment across subregionalstudy area– Greater level of operational detail closer to projectimpact area

Integrated Modeling FrameworkRegional TravelDemand ModelSubarea TDMRefinementMeso-ModelExtractionMeso-Model• Refinement• CalibrationMacro-Level(BPM –TransCAD)Meso-Level(Aimsun)Planning LevelOutputsMicro-ModelExtractionMicrosimulationModelsMicro-Level(Aimsun)

Aimsun Software

Aimsun Advantages• Ability to integrate macro-meso-micro dynamicsimulation• Ability to build on existing Green Light forMidtown model• Integration of traffic and pedestrian simulation(Legion)

Core, Primary, and Secondary Study Areas

Analytical Issues• Origin-destination (O-D) matrix estimationtechniques• Network consistency• Data needs and duration of simulation• Traffic data availability and vehicle types to bemodeled• Level of validation (strategic versus local)• Temporal distribution

Network Development• Network characteristics– Lanes, turning movements, curb activity: Field datacollection– Signal timings: NYC DOT Signals Division– Tunnel operations: Coordination with PA, MTA B+T• Single database for all network characteristics• Predecessor models:– NYMTC BPM– Green Light for Midtown (Aimsun)– CATS (VISSIM)– Lower Manhattan (Paramics)

Mesoscopic Trip Table Development• Validation of NYMTC’s BPM model at theboundaries of the mesoscopic study area• Extracted trip table for meso-model will needadjustment• Origin-destination matrix estimation techniques(ODME)• Traffic data available or new data collectionneeded?• O-D surveys to enhance “seed” table available

Calibration/Validation Data Requirements• Demand and volume:– Traffic flows at individual links and screenlines– Saturation flow information, if available– O-D surveys identifying travel patterns alongcritical corridors such as Trans-Hudson• Traffic characteristics:– Travel speeds along critical corridors– Queues throughout Core study area

Documentation• Network and zone development• Traffic input data• Results of the ODME process, includingfrequency distribution comparisons for the“seed” and final trip tables• Validation– Criteria– Results for mesoscopic and microscopic models• Measures of effectiveness (MOE), includingexport data for HCS analysis

Progress to Date• Developed primary study area network basedon LION• Updated 2005 BPM network to reflect recentNYC DOT network changes• Completed field inventory• Initiated– development of the ODME methodology– development of the taxi revenue/nonrevenue tripmethodology

Project Schedule

Manhattan Traffic Model:Technical OverviewNew York City Department of TransportationPresentation to the BPM Users GroupMarch 4, 2010