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Mohamed S. Mahmoud, M.Sc. Ph.D. Candidate MODELING TRANSIT MODE CHOICE FOR INTER-REGIONAL COMMUTING TRIPS ACT Canada Sustainable Mobility Summit November 2012
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More Transit = More Sustainability 2 of 20
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More Transit = More Sustainability 3 of 20
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How Would we Know? A policy-sensitive comprehensive model is needed WHY? Understand Individuals’ Behaviour Test Travel Demand Management (TDM) Policies and Strategies Estimate Impacts on Transportation Systems 4 of 20
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Travel Demand Models – Discrete Choice Models (Disaggregate) – Behavioural Factors – Limitations: Data Quality and Availability Complex Model Structures Estimation Capabilities Current Sate of Practice Demand Side 5 of 20
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Current Sate of Practice Supply Side Trip Assignment Models (Macro Vs. Micro) – Uni-modal Trip Assignment Traffic Assignment Transit Assignment – Multi-Modal Trip Assignment (Not Only in Theory!) GTHA Model is under development at UofT using MATSim 24-hr Agent-based Activity Scheduler Agent-Based (Disaggregate) Models 6 of 20
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Motivation Why a better framework is needed? Enhanced Model Components (policy-sensitive) Demand and Supply Integration (Feedback) Analysis Resolution (Disaggregate/Agent-based) Detailed Output Universal and Easy to Update 7 of 20
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Framework Components Departure-time Choice Model Mode Choice Model Access Mode and Access Location Choice for Mixed Modes (P&R and K&R) Models Route Choice 8 of 20
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Cross-Regional Commuting Trips Case Study GTHA – Nine Local Transit Agencies – Regional Transit (GO) Cross-Regional Trips – Across Local Transit Jurisdictions – Involve Inter-Modal Interaction 9 of 20
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Inter-Modal Trips 10 of 20
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Enhanced Mode Choice Model Joint Trivariate Choice Decision Structure Each Level Affects the other Two Choices 11 of 20
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Decision Structure 12 of 20
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Conceptual Framework 13 of 20
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Phase I – Understanding Users’ Behaviour Data – Transportation Tomorrow Survey (TTS – 2006) Largest Travel Survey in NA 5% Sample of the GTHA Revealed Preference (RP) Survey 4500 Morning Peak Inter-Regional Trip Records Detailed Transit Information – Morning Peak Hour Level of Service Attributes using GTHA EMME/2 Model 15 of 20
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Phase I – Understanding Users’ Behaviour Demand Model – Three Model Structures D P TD TP TW D: Auto drive all way P: Auto passenger all way TD: Transit with auto driver access (P&R) TP: Transit with auto passenger access (K&R) TW: Transit with walk access Joint Main-Access Modes D P T Nested Main Mode Sequential Main Mode D P W Access Mode D P T TD TP TW Problematic! Access Mode 16 of 20
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Preliminary Results Sequential Model Main Mode Choice Access Mode Choice CoefficientsEstimatet-value TD:(intercept)-3.186827-4.8706*** TW:(intercept)2.3346773.8803*** cost0.5903673.5149*** acost5.882699.2363*** pcost-0.227855-3.1612** wtime-0.084537-3.4083*** atime0.0269661.4606 TD:age25_orless-1.397522-3.7521*** TD:gender_m0.7307122.2554* TW:gender_m0.3049251.0057 TD:trans_pass1.2402563.4447*** TW:trans_pass-0.235584-0.744 TD:n_vehicle0.7185673.5254*** TW:n_vehicle-0.101998-0.5489 TP:time-0.100357-5.4426*** TD:time-0.091635-4.9909*** TW:time-0.104988-5.605*** sd.cost0.2897350.4657 CoefficientsEstimatet-value Drive:(intercept)5.17E-013.5499*** Transit:(intercept)-2.10E-01-0.7716 cost5.25E-022.0709* acost1.41E+02636.2149*** pcost1.46E-040.0105 wtime-1.24E-02-4.6035*** atime-3.20E-02-3.8404*** Drive:age25_orless-1.95E+00-17.2084*** Drive:gender_m1.21E+0011.2037*** Transit:gender_m4.08E-012.6076** Drive:trans_pass-7.19E-01-3.3239*** Transit:trans_pass2.56E+0011.99*** Drive:n_vehicle6.15E-0110.2113*** Transit:n_vehicle-5.18E-01-6.5336*** Passenger:time-1.04E-01-9.5539*** Drive:time-1.01E-01-9.631*** Transit:time-2.79E-02-5.2324*** sd.cost8.88E-022.0126* Suffer From Data Issues 17 of 20
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What is Next? Phase I – (Cont.) Access Location Choice (Under Development) – Generate access location choice set for individuals – Generate level of service attributes of access modes for non-transit trips Trivariate Model Development Phase II Conduct an experimental design ; Stated Preference (SP) Survey Activity-Based Model (update previously developed models) using: – 24-hr activity data – Multi-modal level of service attribute data Equilibrium: Demand – Supply Integration Account for Trip Dynamics and Household Resource Allocation 18 of 20
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Summary A policy-sensitive Comprehensive Modeling Framework Demand Model: Advanced Discrete Choice (behavioural ) Models using 24-hr Activity Data Supply Model: Micro simulation, Dynamic, and Agent- based Multi-modal Models Demand and Supply Integration (Feedback Loop) Case Study: Cross-Regional Commuting Trips (GTHA) 19 of 20
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mohamed.mahmoud@utoronto.ca
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