IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v219y2022ics0951832021007055.html
   My bibliography  Save this article

Robustness of urban railway networks against the cascading failures induced by the fluctuation of passenger flow

Author

Listed:
  • Zhang, Yifan
  • Ng, S. Thomas

Abstract

This paper constructs an urban railway network (URN) as a directed weighted network at different times and studies the dynamic network robustness against the fluctuation of passenger flow-induced cascading failures under different failure modes. The propagation of cascading failure is then imitated through the linear threshold (LT) model, where the influence parameter of edges is defined. In the light of network topology and functionality, two robustness indices, which include the change of edge size in the most connected component (RGCSe) and operational efficiency (ROEt) are employed. By coalescing these two indices, a synthetic operator Rt is proposed to quantify the dynamic TURN robustness comprehensively. The simulation results show that the TURN robustness varies over time. Besides, an increase in the volume of passenger flow can exacerbate the sizes of cascading failure and the impacts on network robustness under different scenarios. Consequently, it is imperative to examine the impacts of time-varying cascading failure on URN robustness. The findings of this research are widely applicable to other networked systems.

Suggested Citation

  • Zhang, Yifan & Ng, S. Thomas, 2022. "Robustness of urban railway networks against the cascading failures induced by the fluctuation of passenger flow," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  • Handle: RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021007055
    DOI: 10.1016/j.ress.2021.108227
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021007055
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2021.108227?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chan, Ho-Yin & Chen, Anthony & Li, Guoyuan & Xu, Xiangdong & Lam, William, 2021. "Evaluating the value of new metro lines using route diversity measures: The case of Hong Kong's Mass Transit Railway system," Journal of Transport Geography, Elsevier, vol. 91(C).
    2. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    3. Zhang, Yifan & Ng, S. Thomas, 2021. "A hypothesis-driven framework for resilience analysis of public transport network under compound failure scenarios," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    4. Wandelt, Sebastian & Shi, Xing & Sun, Xiaoqian, 2021. "Estimation and improvement of transportation network robustness by exploiting communities," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    5. Huang, Wencheng & Zhou, Bowen & Yu, Yaocheng & Sun, Hao & Xu, Pengpeng, 2021. "Using the disaster spreading theory to analyze the cascading failure of urban rail transit network," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. 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.
    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. Shen, Yi & Yang, Huang & Ren, Gang & Ran, Bin, 2024. "Model cascading overload failure and dynamic vulnerability analysis of facility network of metro station," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Chan, Ho-Yin & Ma, Hanxi & Zhou, Jiangping, 2024. "Resilience of socio-technical transportation systems: A demand-driven community detection in human mobility structures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    3. Wang, Ziyulong & Huang, Ketong & Massobrio, Renzo & Bombelli, Alessandro & Cats, Oded, 2024. "Quantification and comparison of hierarchy in Public Transport Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    4. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Zhang, Lin & Xu, Min & Wang, Shuaian, 2023. "Quantifying bus route service disruptions under interdependent cascading failures of a multimodal public transit system based on an improved coupled map lattice model," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    7. Zhang, Jianhua & Min, Qinjie & Zhou, Yu & Cheng, Lilai, 2024. "Vulnerability assessments of urban rail transit networks based on extended coupled map lattices with evacuation capability," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    8. Li, Jin-Yang & Teng, Jing & Wang, Hui, 2024. "Measuring route diversity in spatial and spatial-temporal public transport networks," Transport Policy, Elsevier, vol. 146(C), pages 42-58.
    9. Lu, Bo & Sun, Yue & Wang, Huipo & Wang, Jian-Jun & Shuai Liu, Samuel & Cheng, T.C.E., 2024. "Dynamic resilience analysis of the liner shipping network: From structure to cooperative mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
    10. 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).
    11. 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.
    12. Batac, Rene C. & Cirunay, Michelle T., 2022. "Shortest paths along urban road network peripheries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    13. Liu, Xueli & Jiang, Chunxia & Wang, Feng & Yao, Shujie, 2021. "The impact of high-speed railway on urban housing prices in China: A network accessibility perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 84-99.
    14. Yanjie Zhang & Bilal M. Ayyub & Dongming Zhang & Hongwei Huang & Yalda Saadat, 2019. "Impact of Water Level Rise on Urban Infrastructures: Washington, DC, and Shanghai as Case Studies," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2718-2731, December.
    15. Wang, Zhiru & Niu, Fangyan & Yang, Lili & Su, Guofeng, 2020. "Modeling a subway network: A hot-point attraction-driven evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    16. Ding Luo & Oded Cats & Hans Lint, 2020. "Can passenger flow distribution be estimated solely based on network properties in public transport systems?," Transportation, Springer, vol. 47(6), pages 2757-2776, December.
    17. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    18. Hu, Baoyu & Feng, Shumin & Li, Jinyang & Zhao, Hu, 2018. "Statistical analysis of passenger-crowding in bus transport network of Harbin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 426-438.
    19. 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.
    20. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

    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:eee:reensy:v:219:y:2022:i:c:s0951832021007055. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.