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Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

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  • Xiangming Yao
  • Baomin Han
  • Dandan Yu
  • Hui Ren

Abstract

The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA) method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

Suggested Citation

  • Xiangming Yao & Baomin Han & Dandan Yu & Hui Ren, 2017. "Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-15, February.
  • Handle: RePEc:hin:jnddns:2890814
    DOI: 10.1155/2017/2890814
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    Cited by:

    1. Paulsen, Mads & Rasmussen, Thomas Kjær & Nielsen, Otto Anker, 2021. "Impacts of real-time information levels in public transport: A large-scale case study using an adaptive passenger path choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 155-182.

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