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Simulation Study on Topology Characteristics and Cascading Failure of Hefei Subway Network

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  • Xiaohong Yin

    (School of Economics and Management, Liaoning University of Technology, Jinzhou 121001, China)

  • Jiakun Wu

    (School of Economics and Management, Liaoning University of Technology, Jinzhou 121001, China)

Abstract

The structural characteristics and robustness of subway networks are important for improving the safety and efficiency of subway operations. Based on complex network theory, this study analyzed the structural characteristics of the Hefei subway network and evaluated its robustness after suffering from accidents. Specifically: (1) A model of the Hefei subway network was established using the space-L method, and its topological structural characteristics were quantitatively analyzed; (2) An improved cascading failure simulation model was established, and a node importance evaluation system was developed to identify the critical nodes in the Hefei subway network; (3) A simulation analysis was conducted to evaluate the robustness of the Hefei subway network under different scenarios. The results show that the Hefei subway network is different from a scale-free network and small-world network, and the structure was most severely damaged when facing attacks against critical nodes in the cascading failure scenario. Moreover, as the value of the parameter of the control node capacity in the cascade failure model varied, the degree of damage to the subway network also varied considerably. We believe that the results obtained from the study could provide a reference for the construction and planning of the subway network.

Suggested Citation

  • Xiaohong Yin & Jiakun Wu, 2022. "Simulation Study on Topology Characteristics and Cascading Failure of Hefei Subway Network," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:422-:d:1016291
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    References listed on IDEAS

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    1. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    2. Yingying Xing & Jian Lu & Shengdi Chen & Sunanda Dissanayake, 2017. "Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro," Public Transport, Springer, vol. 9(3), pages 501-525, October.
    3. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    4. Jianhua Zhang & Ziqi Wang & Shuliang Wang & Shengyang Luan & Wenchao Shao, 2020. "Vulnerability Assessments of Urban Rail Transit Networks Based on Redundant Recovery," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    5. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
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