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Using the disaster spreading theory to analyze the cascading failure of urban rail transit network

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  • Huang, Wencheng
  • Zhou, Bowen
  • Yu, Yaocheng
  • Sun, Hao
  • Xu, Pengpeng

Abstract

A new dynamic model is established to formulate the cascading failure in the urban rail transit network based on the disaster spreading theory. Firstly, the weighted urban rail transit network by considering the time cost of each effective path is established, the transfer station and turn back station on the topological network are handled specifically, the Dijkstra algorithm is designed to solve the shortest path of each Origin-Destination. Then, the cascading failure model based on disaster spreading theory is established. Five factors including the failure evolution process with time, self-recovery ability of the nodes, failures spreading mechanism, passenger volume changes and the internal random noises by other influence factors are fully considered in this model. Finally, a real-world case study is conducted by using Chengdu Metro Network as the background. Eight simulation scenarios are established, the output is statistical number of failed stations. The results show that, the failed stations number has the greatest scale when fixed transfer stations are attacked. There is no obvious functional relationship between the scale of failure stations and self-recovery factor, and there is a positive correlation between self-recovery factor and cascading failure scale. Based on the results, five emergency resources allocation strategies are proposed.

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  • 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).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s095183202100346x
    DOI: 10.1016/j.ress.2021.107825
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    16. Ma, Zhiao & Yang, Xin & Wu, Jianjun & Chen, Anthony & Wei, Yun & Gao, Ziyou, 2022. "Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model," Transport Policy, Elsevier, vol. 129(C), pages 38-50.
    17. 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).
    18. Wang, Ziqi & Pei, Yulong & Zhang, Jianhua & Dong, Chuntong & Liu, Jing & Zhou, Dongyue, 2024. "Vulnerability analysis of public transit systems from the perspective of the traffic situation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
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