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Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro

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  • Zhang, Jianhua
  • Wang, Meng

Abstract

This paper employs system science and complex network theory to abstract the topological structure and to analyze the connectivity of urban rail transit networks. Meanwhile, movingblock technology is applied to calculate the transportation functionality and to investigate the static and dynamic vulnerability based on transportation functionality of urban rail transit networks. Considering Nanjing metro network as example, the results show that the connectivity of Nanjing metro network is very poor. For static failures, Nanjing metro network is very vulnerable when suffering malicious attacks, and the highest load node-based attacks can result in more damages than the largest degree node-based attacks. For dynamic failures, the results show that the transportation functionality becomes larger and larger with the increase of the control parameter of load capacity, which illustrates that the reliability becomes higher and higher with the increase of the construction cost. Therefore, we can declare that there exists a tradeoff between the reliability and construction cost of urban rail transit networks.

Suggested Citation

  • Zhang, Jianhua & Wang, Meng, 2019. "Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313639
    DOI: 10.1016/j.physa.2019.122367
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    6. 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.
    7. Zhang, Jianhua & Wang, Ziqi & Wang, Shuliang & Shao, Wenchao & Zhao, Xun & Liu, Weizhi, 2021. "Vulnerability assessments of weighted urban rail transit networks with integrated coupled map lattices," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    8. De Bona, Anderson Andrei & de Oliveira Rosa, Marcelo & Ono Fonseca, Keiko Verônica & Lüders, Ricardo, 2021. "A reduced model for complex network analysis of public transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    9. 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.
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