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Subway Multi-Station Coordinated Dynamic Control Method Considering Transfer Inbound Passenger Flow

Author

Listed:
  • Linghui Xu

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China)

  • Jia Lu

    (Ningbo Regional Railway Investment and Development Co., Ltd., Ningbo 315111, China)

  • Shuichao Zhang

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China)

  • Gang Ren

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 211189, China)

  • Kangkang He

    (School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China)

Abstract

The prominent contradiction between passenger demand and capacity in rush hours at subway stations causes inconveniences to travel and even leads to safety risks. Existing research on the cooperative control of passenger flow at stations mostly focuses on a single direction, rarely considering transfer passenger flow control. This study formulated a coordinated dynamic control strategy for multiple stations in both directions as a deterministic mathematical programming model to optimise the crowded passenger flow. The optimisation objectives were set as the warning levels of crowded passenger flow and the detention time of all passengers. The constraints included limitations on station service capacity, train capacity, and the number of people boarding trains. Additionally, considering separate control over the transfer inbound passenger flow at transfer stations, an upward- and downward-direction coordinated dynamic control model was constructed. Numerical experiments based on real-world data from the Nanjing Metro Line 1 were conducted to investigate the effectiveness of the proposed cooperative control scheme and evaluate its performance.

Suggested Citation

  • Linghui Xu & Jia Lu & Shuichao Zhang & Gang Ren & Kangkang He, 2024. "Subway Multi-Station Coordinated Dynamic Control Method Considering Transfer Inbound Passenger Flow," Sustainability, MDPI, vol. 16(24), pages 1-21, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:11292-:d:1550705
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    References listed on IDEAS

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    1. Hongjiao Xue & Limin Jia & Jianyuan Guo, 2020. "Adaptive Multilevel Collaborative Passenger Flow Control in Peak Hours for a Subway Line," Advances in Mathematical Physics, Hindawi, vol. 2020, pages 1-16, September.
    2. Shi, Jungang & Yang, Lixing & Yang, Jing & Gao, Ziyou, 2018. "Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 26-59.
    3. Liu, Renming & Li, Shukai & Yang, Lixing, 2020. "Collaborative optimization for metro train scheduling and train connections combined with passenger flow control strategy," Omega, Elsevier, vol. 90(C).
    4. Niu, Huimin & Zhou, Xuesong & Gao, Ruhu, 2015. "Train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: Nonlinear integer programming models with linear constraints," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 117-135.
    5. Jianghua Gao & Limin Jia & Jianyuan Guo, 2019. "Applying System Dynamics to Simulate the Passenger Flow in Subway Stations," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-14, December.
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