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Evaluation Method for Node Importance of Urban Rail Network Considering Traffic Characteristics

Author

Listed:
  • Ting Chen

    (School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Jianxiao Ma

    (School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Zhenjun Zhu

    (School of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Xiucheng Guo

    (School of Transportation, Southeast University, Nanjing 210096, China)

Abstract

As a sustainable means of public transport, the safety of the urban rail transit is a significant section of public safety and is highly important in urban sustainable development. Research on the importance of urban rail stations plays an important role in improving the reliability of urban rail networks. This paper proposed an improved method for evaluating the importance of urban rail stations in a topology network, which was used to identify the key stations that affect the urban rail network performance. This method was based on complex network theory, considering the traffic characteristics of the urban rail network that runs on specific lines and integrating the structural characteristics and interrelationship of the lines where the stations are located. Hereafter, this method will be abbreviated as CLI. In order to verify that the high importance stations evaluated by this method were the key stations that had a great impact on the urban rail network performance, this paper designed a comparative attack experiment of betweenness centrality and CLI. The experiment was carried out by taking the Suzhou Rail Transit (SZRT) network as an example and the largest connected subgraph as well as the network efficiency as indicators to measure the network performance. The results showed that CLI had a greater impact on network performance and could better evaluate the key stations in the urban rail network than node degree and betweenness centrality.

Suggested Citation

  • Ting Chen & Jianxiao Ma & Zhenjun Zhu & Xiucheng Guo, 2023. "Evaluation Method for Node Importance of Urban Rail Network Considering Traffic Characteristics," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3582-:d:1069406
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    References listed on IDEAS

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    1. Zhang, Yanjie & Ayyub, Bilal M. & Saadat, Yalda & Zhang, Dongming & Huang, Hongwei, 2020. "A double-weighted vulnerability assessment model for metrorail transit networks and its application in Shanghai metro," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    2. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. 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.
    4. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    5. 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.
    6. 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.
    7. Fei, Liguo & Deng, Yong, 2017. "A new method to identify influential nodes based on relative entropy," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 257-267.
    8. Shaopei Chen & Dachang Zhuang, 2020. "Evolution and Evaluation of the Guangzhou Metro Network Topology Based on an Integration of Complex Network Analysis and GIS," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    9. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    10. 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.
    11. Li, W. & Cai, X., 2007. "Empirical analysis of a scale-free railway network in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 693-703.
    12. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    13. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
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    5. 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.

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