Integrated simulation-based dynamic traffic and transit assignment model for large-scale network

Author:

Kamel Islam11,Shalaby Amer1,Abdulhai Baher11

Affiliation:

1. University of Toronto, 35 St. George Street, Toronto, ON M5S 1A4, Canada.

Abstract

Although the traffic and transit assignment processes are intertwined, the interactions between them are usually ignored in practice, especially for large-scale networks. In this paper, we build a simulation-based traffic and transit assignment model that preserves the interactions between the two assignment processes for the large-scale network of the Greater Toronto Area during the morning peak. This traffic assignment model is dynamic, user-equilibrium seeking, and includes surface transit routes. It utilizes the congested travel times, determined by the dynamic traffic assignment, rather than using predefined timetables. Unlike the static transit assignment models, the proposed transit model distinguishes between different intervals within the morning peak by using the accurate demand, transit schedule, and time-based road level-of-service. The traffic and transit assignment models are calibrated against actual field observations. The resulting dynamic model is suitable for testing different demand management strategies that impose dynamic changes on multiple modes simultaneously.

Publisher

Canadian Science Publishing

Subject

General Environmental Science,Civil and Structural Engineering

Reference25 articles.

1. Abdelgawad, H., and Abdulhai, B. 2009. Optimal spatio-temporal evacuation demand management: methodology and case study in Toronto. In The 88th Transportation Research Board Meeting, 11–15 January 2009, Washington, D.C. Available from https://trid.trb.org/view/881172.

2. Aboudina, A. 2016. Optimized time-dependent congestion pricing system for large networks: integrating distributed optimization, departure time choice, and dynamic traffic assignment in the Greater Toronto Area. Ph.D. thesis, Department of Civil Engineering, University of Toronto, Toronto, Ontario, Canada.

3. Harnessing the Power of HPC in Simulation and Optimization of Large Transportation Networks: Spatio-Temporal Traffic Management in the Greater Toronto Area

4. Modeling Transit Trip Time Using Archived Bus Dispatch System Data

5. Chiu, Y.C., Bottom, J., Mahut, M., Paz, A., Balakrishna, R., Waller, T., and Hicks, J. 2011. Dynamic traffic assignment: a primer. Transportation Research Board, Washington, D.C.

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