IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i19p8918-d1766654.html
   My bibliography  Save this article

A Passenger Flow-Based Resilience Measurement Model for Sustainable Operation of the Metro Station

Author

Listed:
  • Kuo Han

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Qinghuai Liang

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Jinlei Zhang

    (School of Systems Science, Beijing Jiaotong University, Beijing 100044, China)

  • Songsong Li

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Metro stations serve as critical hubs for passenger gathering and scattering. Under disturbing scenarios, a station’s ability to respond to disturbances, named resilience, fundamentally governs the operational stability, sustainability and emergency performance of the metro network. Existing metro network resilience studies typically treated stations merely as topological nodes, making it impossible to account for the internal passenger flow organization and facility capacities of the station. The resilience of the station itself cannot be characterized and quantified. This study focuses on the metro station’s resilience. From the perspective of sustainable operation, considering the passenger flow management of the station, the station’s resilience is defined as the ability of the station to maintain its basic service capabilities and minimize the number of delayed passengers within the station during disturbances. A passenger delay coefficient is introduced to quantify variations in passenger delay volumes within the station. The total number of passengers entering and leaving a station is used to quantify its service capacity. A resilience measurement model for the station is constructed by coupling the passenger delay coefficient and the service capacity. A case study of a transfer station experiencing a sudden passenger surge is conducted for model validation, considering passenger flow control measures and train capacity constraints. The results demonstrate that the model measures the station’s resilience across varying passenger flow management strategies effectively. This study provides a quantitative tool for measuring metro station resilience, enabling emergency responses, operational optimization and policy formulation that support the sustainable and stable operation of metro stations and networks.

Suggested Citation

  • Kuo Han & Qinghuai Liang & Jinlei Zhang & Songsong Li, 2025. "A Passenger Flow-Based Resilience Measurement Model for Sustainable Operation of the Metro Station," Sustainability, MDPI, vol. 17(19), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8918-:d:1766654
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/19/8918/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/19/8918/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liudan Jiao & Yinghan Zhu & Xiaosen Huo & Ya Wu & Yu Zhang, 2023. "Resilience assessment of metro stations against rainstorm disaster based on cloud model: a case study in Chongqing, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(2), pages 2311-2337, March.
    2. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    3. Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    5. D’Lima, Minette & Medda, Francesca, 2015. "A new measure of resilience: An application to the London Underground," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 35-46.
    6. Chengli Cong & Xuan Li & Shiwei Yang & Quan Zhang & Lili Lu & Yang Shi, 2022. "Impact Estimation of Unplanned Urban Rail Disruptions on Public Transport Passengers: A Multi-Agent Based Simulation Approach," IJERPH, MDPI, vol. 19(15), pages 1-25, July.
    7. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
    8. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qingjie Qi & Yangyang Meng & Xiaofei Zhao & Jianzhong Liu, 2022. "Resilience Assessment of an Urban Metro Complex Network: A Case Study of the Zhengzhou Metro," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
    2. Xu, Peng-Cheng & Lu, Qing-Chang & Feng, Tao & Li, Jing & Li, Gen & Xu, Xin, 2024. "Resilience analysis of metro stations integrating infrastructures and passengers," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    3. Yangyang Meng & Xiaofei Zhao & Jianzhong Liu & Qingjie Qi, 2023. "Dynamic Influence Analysis of the Important Station Evolution on the Resilience of Complex Metro Network," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    4. Junhong Hu & Mingshu Yang & Yunzhu Zhen, 2024. "A Review of Resilience Assessment and Recovery Strategies of Urban Rail Transit Networks," Sustainability, MDPI, vol. 16(15), pages 1-16, July.
    5. Zheng, Shuai & Liu, Yugang & Lin, Yexin & Wang, Qiang & Yang, Hongtai & Chen, Bin, 2022. "Bridging strategy for the disruption of metro considering the reliability of transportation system: Metro and conventional bus network," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    6. Wang, Yiran & Mo, Pengli & Chen, Jingxu & Liu, Zhiyuan, 2025. "Managing oversaturation in BRT corridors: A new approach of timetabling for resilience enhancement using a tailored integer L-shaped algorithm," European Journal of Operational Research, Elsevier, vol. 320(1), pages 219-238.
    7. Xinyao Yin & Junhua Chen & Yuexuan Li, 2024. "Simulation-Based Resilience Evaluation for Urban Rail Transit Transfer Stations," Sustainability, MDPI, vol. 16(9), pages 1-22, April.
    8. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    9. Zhang, Li & Chen, Tingting & Liu, Zhongshan & Yu, Bin & Wang, Yunpeng, 2024. "Analysis of multi-modal public transportation system performance under metro disruptions: A dynamic resilience assessment framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    10. Knoester, Max J. & Bešinović, Nikola & Afghari, Amir Pooyan & Goverde, Rob M.P. & van Egmond, Jochen, 2024. "A data-driven approach for quantifying the resilience of railway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    11. Chen, Daqiang & Sun, Danzhi & Yin, Yunqiang & Dhamotharan, Lalitha & Kumar, Ajay & Guo, Yihan, 2022. "The resilience of logistics network against node failures," International Journal of Production Economics, Elsevier, vol. 244(C).
    12. Ma, Zhiao & Yang, Xin & Chen, Anthony & Zhu, Tianlei & Wu, Jianjun, 2025. "Assessing the resilience of multi-modal transportation networks with the integration of urban air mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 195(C).
    13. Xiaoyou Wang & Jiahe Tian & Enze Liu, 2025. "Enhancing the Resilience of Intercity Transit System by Integrated Multimodal Emergency Dispatching and Passenger Assignment," Sustainability, MDPI, vol. 17(13), pages 1-18, June.
    14. Wang, Ying & Zhao, Ou & Zhang, Limao, 2024. "Modeling urban rail transit system resilience under natural disasters: A two-layer network framework based on link flow," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    15. Meng, Yangyang & Zhao, Xiaofei & Liu, Jianzhong & Qi, Qingjie & Zhou, Wei, 2023. "Data-driven complexity analysis of weighted Shenzhen Metro network based on urban massive mobility in the rush hours," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    16. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    17. Abdelaty, Hatem & Mohamed, Moataz & Ezzeldin, Mohamed & El-Dakhakhni, Wael, 2022. "Temporal robustness assessment framework for city-scale bus transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    18. Liping Ge & Stefan Voß & Lin Xie, 2022. "Robustness and disturbances in public transport," Public Transport, Springer, vol. 14(1), pages 191-261, March.
    19. Liu, Enze & Barker, Kash & Chen, Hong, 2022. "A multi-modal evacuation-based response strategy for mitigating disruption in an intercity railway system," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    20. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8918-:d:1766654. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.