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Exploring the Relationships between the Topological Characteristics of Subway Networks and Service Disruption Impact

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  • Zhiru Wang

    (School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)

  • Wubin Ma

    (Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China)

  • Albert Chan

    (Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China)

Abstract

Although numerous studies have considered the topological characteristics and the impact of disruptions in subway systems, their results have not been verified by empirical data. To address this limitation, we used a data set containing 392 detailed records of disruptions to subway services in Beijing from 2011 to 2017. The Spearman rank correlation coefficient analysis results indicate that the delay duration exhibits no significant relationship with the topological characteristics, whereas the reverse is true for the relationship between the number of affected trains and the topological characteristics. The results also demonstrate that subway network expansion will not result in a paradox between convenience and vulnerability from an actual data perspective. Moreover, contrary to previous research results, no significant relationship was found to exist between service interruption impact and the transit and key bridge stations. However, a high degree of clustering, characterized by redundant tracks between neighbours, tends to provide protection against service disruption for stations. In terms of the spatial variation, the influence of the disruption is greater when the station is further from the centre of the line. These results can support sustainable design in subway network planning.

Suggested Citation

  • Zhiru Wang & Wubin Ma & Albert Chan, 2020. "Exploring the Relationships between the Topological Characteristics of Subway Networks and Service Disruption Impact," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:3960-:d:356985
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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. Zhang, X. & Miller-Hooks, E. & Denny, K., 2015. "Assessing the role of network topology in transportation network resilience," Journal of Transport Geography, Elsevier, vol. 46(C), pages 35-45.
    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. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    5. Jin, Jian Gang & Tang, Loon Ching & Sun, Lijun & Lee, Der-Horng, 2014. "Enhancing metro network resilience via localized integration with bus services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 63(C), pages 17-30.
    6. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    7. Cats, Oded & Vermeulen, Alex & Warnier, Martijn & van Lint, Hans, 2020. "Modelling growth principles of metropolitan public transport networks," Journal of Transport Geography, Elsevier, vol. 82(C).
    8. 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.
    9. Zhang, Jianhua & Xu, Xiaoming & Hong, Liu & Wang, Shuliang & Fei, Qi, 2011. "Networked analysis of the Shanghai subway network, in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4562-4570.
    10. Zhang, Wen-Yao & Wei, Zong-Wen & Wang, Bing-Hong & Han, Xiao-Pu, 2016. "Measuring mixing patterns in complex networks by Spearman rank correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 440-450.
    11. Yu Wei & Sun Ning, 2018. "Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    12. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.
    13. Cats, O., 2016. "The robustness value of public transport development plans," Journal of Transport Geography, Elsevier, vol. 51(C), pages 236-246.
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    2. Jean-Philippe Meloche & Vincent Trotignon & François Vaillancourt, 2021. "Densification ou prolongement des réseaux de transport structurants ? Une recension des écrits sur les coûts et les bénéfices attendus," CIRANO Project Reports 2020rp-28, CIRANO.

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