IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3582-d1069406.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3582/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3582/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lan Luan & Guixiang Shen & Yingzhi Zhang, 2024. "A Comprehensive Evaluation Method of Machining Center Components’ Importance Based on Combined Variable Weight," Mathematics, MDPI, vol. 12(2), pages 1-19, January.
    2. Junhong Hu & Mingshu Yang & Yunzhu Zhen, 2024. "A Review of Resilience Assessment and Recovery Strategies of Urban Rail Transit Networks," Sustainability, MDPI, vol. 16(15), pages 1-16, July.
    3. 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.
    4. Hong Zhang & Lu Lu, 2024. "Modeling and Analysis of Public Transport Network in Hohhot Based on Complex Network," Sustainability, MDPI, vol. 16(20), pages 1-15, October.
    5. Yunfang Ma & Jose M. Sallan & Oriol Lordan, 2024. "Rail Transit Networks and Network Motifs: A Review and Research Agenda," Sustainability, MDPI, vol. 16(9), pages 1-21, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    2. 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).
    3. Xu, Chen & Xu, Xueguo, 2024. "A two-stage resilience promotion approach for urban rail transit networks based on topology enhancement and recovery optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    4. Noguchi, Hiroki & Fuse, Masaaki, 2020. "Rethinking critical node problem for railway networks from the perspective of turn-back operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    5. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    6. Yingying Xing & Jian Lu & Shendi Chen, 2016. "Weighted Complex Network Analysis of Shanghai Rail Transit System," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-8, August.
    7. 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).
    8. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    9. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    10. Zhang, Jianhua & Wang, Shuliang & Zhang, Zhaojun & Zou, Kuansheng & Shu, Zhan, 2016. "Characteristics on hub networks of urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 502-507.
    11. 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).
    12. 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.
    13. Hu, Jie & Wen, Weiping & Zhai, Changhai & Pei, Shunshun, 2024. "Post-earthquake functionality assessment for urban subway systems: Incorporating the combined effects of seismic performance of structural and non-structural systems and functional interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    14. 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.
    15. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    16. Tang, Jinjun & Li, Zhitao & Gao, Fan & Zong, Fang, 2021. "Identifying critical metro stations in multiplex network based on D–S evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    17. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    18. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    19. Wang, Zhiru & Niu, Fangyan & Yang, Lili & Su, Guofeng, 2020. "Modeling a subway network: A hot-point attraction-driven evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3582-:d:1069406. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.