GIS Estimation of Transit Access Parameters for Mode Choice Models

Parsons BrinckerhoffChicago, Illinois

GIS Estimation of Transit Access Parameters for Mode Choice Models

GIS in Transit ConferenceOctober 16-17, 2013Washington, DC 1Presentation OutlineOverview of the Chicago Metropolitan Agency for Planning mode choice modelThe transit access sub-modelAccess modesData inputs to estimate access distancesGIS estimation of input parameters in TransCAD/Maptitude Sample plotsExtensions

2CMAP Trip Based ModelPRE-DISTRIBUTIONTravel Times and Distances by ModeTRIP DISTRIBUTIONPerson Trip TablesMODE CHOICEPerson Trip Tablesby ModeNETWORK ASSIGNMENT3Mode Choice Estimation4The CMAP model is a trip based modelHome-work: transit, single occupant, ride share and carpool autoHome-other: transit and autoNon-home: transit and autoSimulates individuals choice of mode per tripEvaluate logit model for probabilitiesMonte Carlo methodPre-distribution model is the front end of the mode choice modelSimulates 100 trips between zone pairsEstimates average travel times and distances by mode

Model Logic Flow5 Read Origin Files(Origin to All Destinations)1.Person Trips2.Highway Times/Distances3.Line-Haul Transit Service AttributesFirst, Priority and Last ModeIn-Vehicle and Out-of-Vehicle TimeFirst HeadwayFaresRepeat for all O-D TripsRepeat for allOrigin ZonesSet Program OptionsDestination ZoneZone and Transit/Hwy System ParametersOrigin ZoneSelect TripEvaluate Logit Mode Choice EquationSimulate ChoiceAdd Trip to Trip TableAll Trips to Destination Zone Simulated?Repeat for allDestination ZonesNoCompute Non-CBDParking Walk Timeand CostSimulate CBDParking Walk Timeand CostCompute Auto Operating CostsSimulate Transit Access/Egress AttributesIn-Vehicle TimeOut-of-Vehicle TimeFaresYesAccess/Egress Sub-modelsSub-Models6Auto operating costs$=f(speed)*distanceRelationship between $/mile and speed is inputSpeed determined from skimming network CBD parkingRelationship between walk distance and CBD parking cost is input by zoneProportion of free CBD parking and auto occupancy also input by zoneFree versus pay CBD parking determined by Monte Carlo simulationPay CBD parking costs and walking distance determined by:Value of time based on incomeReduction in parking costs due to parking further away from destinationAuto occupancy also determined by Monte Carlo simulation Non-CBD parkingFixed rates depending on locationAverage auto occupancy by trip typeTransit access costs and timesTransit Access Sub-Model7InputsFirst, last, and priority (modes ordered in the sequence commuter rail, rail transit, express bus, local bus) modeAverage speeds for transit access modes walk, bus and autoFaresAuto operating costsDrivers value of timePark and ride ratesWalk times from park and rideDistance distribution parametersCosts and times for alternative transit access modes walk, bus, park and ride, kiss and ride, feeder bus (peak only)Least costly transit access mode selected for simulated trip

Model Estimation of Distance to Transit 8Many of the transit access mode costs depend on distance to stops and rail stationsOften use zone average distance to nearest stop station

Challenge to estimate accurate access distancesAverage zone distances often introduce a bias against transit

Relatively large transportation planning zonesLocation of zone centroids often reflect where activities are located not where transit is an alternative

ZoneCentroidAccess Sub-Model Calculations9Mean distance to stop/station and standard deviation of distance are input for each zoneNormal distribution randomly sampled for each simulated tripModesCommuter rail stationRail transit stationBus stopFeeder bus stopPark and ride station

Access Distance Approach10Caliper Corporation Maptitude/TransCADMethodologyPoint layer of stations or stopsCreate areas of influenceOverlay areas of influence over sub-zones (quarter-sections)Assign station/stop to subzone and calculate access distanceEstimate zone mean access distances from subzone distances within zoneEstimate standard deviation of access distance from subzones distances plus intra-subzone variance

Metra Station Point Layer11

Metra Station Areas of Influence12

Influence Areas13Thiessen or Voronoi polygonsEach point within polygon is closer to station than any other stationSubzones Within CMAP Study Area14

Subzone-Metra Station Match15

Regional Model Zones16

Model Zone Parameters17

Rail Transit and Bus Areas of Influence18

CTA Rail TransitCTA and PACE Bus1819

Rail Transit Extension Example: Initial Areas of InfluenceRail Transit Extension Example: Added Stations20

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Rail Transit Extension Example: Revised Areas of Influence22Rail Transit Extension Example: Impact on Adjacent Line

Final Thoughts23Systematic analytic approach that captures the differences between regional transit alternativesReproducibleNot dependent on planning judgment Directly linked to model coded transit networksGeneral approach could be implemented in a variety of applicationsImprove access calculations in conventional modelsComponent of activity based models simulation of individual movementsSubstitute General Transit Feed Specification (GTFS) data for model networks Questions?24Ron EashParsons BrinckerhoffChicago, ILeashrw@pbworld.com