Mohamed S. Mahmoud, M.Sc. Ph.D. Candidate MODELING TRANSIT MODE CHOICE FOR INTER-REGIONAL COMMUTING TRIPS ACT Canada Sustainable Mobility Summit November.

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Presentation transcript:

Mohamed S. Mahmoud, M.Sc. Ph.D. Candidate MODELING TRANSIT MODE CHOICE FOR INTER-REGIONAL COMMUTING TRIPS ACT Canada Sustainable Mobility Summit November 2012

More Transit = More Sustainability 2 of 20

More Transit = More Sustainability 3 of 20

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

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

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

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

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

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

Inter-Modal Trips 10 of 20

Enhanced Mode Choice Model Joint Trivariate Choice Decision Structure Each Level Affects the other Two Choices 11 of 20

Decision Structure 12 of 20

Conceptual Framework 13 of 20

14 of 20

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

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

Preliminary Results Sequential Model Main Mode Choice Access Mode Choice CoefficientsEstimatet-value TD:(intercept) *** TW:(intercept) *** cost *** acost *** pcost ** wtime *** atime TD:age25_orless *** TD:gender_m * TW:gender_m TD:trans_pass *** TW:trans_pass TD:n_vehicle *** TW:n_vehicle TP:time *** TD:time *** TW:time *** sd.cost CoefficientsEstimatet-value Drive:(intercept)5.17E *** Transit:(intercept)-2.10E cost5.25E * acost1.41E *** pcost1.46E wtime-1.24E *** atime-3.20E *** Drive:age25_orless-1.95E *** Drive:gender_m1.21E *** Transit:gender_m4.08E ** Drive:trans_pass-7.19E *** Transit:trans_pass2.56E *** Drive:n_vehicle6.15E *** Transit:n_vehicle-5.18E *** Passenger:time-1.04E *** Drive:time-1.01E *** Transit:time-2.79E *** sd.cost8.88E * Suffer From Data Issues 17 of 20

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

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