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Risk Assessment of Passenger Flow in an Urban Rail Transit System: Indicators, Application, and Analysis

In: Advances in Best-Worst Method

Author

Listed:
  • Liwei Duan

    (Chongqing Jiaotong University)

  • Diejie Fu

    (Chongqing Jiaotong University)

  • Kaiping Zhang

    (Chongqing Jiaotong University)

  • Zhen Li

    (Chongqing Jiaotong University)

Abstract

Risks due to passenger flow have become an important factor affecting the operational safety of urban rail transit (URT) systems in China. Although several studies have focused on the problems raised by the volume of passenger flow, few have studied potential risks caused by the imbalance of passenger flow in time and space. This paper designs a multidimensional, multilevel risk assessment framework of passenger flow in a URT system, including 3 levels (stations, lines and the network) and 27 indicators. Additionally, the BWM (best and worst method) is selected as the evaluation method, and then the optimal weights of each index are calculated through pairwise comparison with the best and worst indicators. Finally, with the Chongqing URT system as a case study, 1920 sets of data from April 2018 are obtained for four scenarios (weekends, holidays, workdays, and the days before a holiday). The evaluation results show that the passenger flow risks on workdays and the days before a holiday present obvious morning and evening peaks. The extreme value of the passenger flow risk at the station level appears during the evening peak on days before a holiday, and the extreme values of passenger flow risk on the line and network level appear during the morning peak of workdays. Further comparison shows that the trends of the passenger flow risk on weekends, holidays, workdays and the days before a holiday are consistent with the result from a single indicator (inbound passenger flow).

Suggested Citation

  • Liwei Duan & Diejie Fu & Kaiping Zhang & Zhen Li, 2022. "Risk Assessment of Passenger Flow in an Urban Rail Transit System: Indicators, Application, and Analysis," Lecture Notes in Operations Research, in: Jafar Rezaei & Matteo Brunelli & Majid Mohammadi (ed.), Advances in Best-Worst Method, pages 79-94, Springer.
    • Handle: RePEc:spr:lnopch:978-3-030-89795-6_7
    DOI: 10.1007/978-3-030-89795-6_7
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