Hub Node Identification in Urban Rail Transit Network Evolution Using a Ridership-Weighted Network

被引:0
|
作者
Tian, Tian [1 ]
Cheng, Yanqiu [1 ]
Liang, Yichen [1 ]
Ma, Chen [1 ]
Chen, Kuanmin [1 ]
Hu, Xianbiao [2 ]
机构
[1] Changan Univ, Coll Transportat Engn, Xian, Shaanxi, Peoples R China
[2] Penn State Univ, Dept Civil & Environm Engn, University Pk, PA USA
基金
中国国家自然科学基金;
关键词
planning and analysis; transportation planning analysis and application; decision tools; project selection; public transportation; planning and development; station; VULNERABILITY; RESILIENCE;
D O I
10.1177/03611981231217500
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
With the development of the urban rail transit network (URTN), the network structure and performance have changed, and the node importance has also been redistributed. However, little research has been done on how hub nodes change as the network develops over a lengthy period. Moreover, most hub node identification methods only focus on the analysis of topological networks or single-dimension measurements, resulting in inaccurate identification results. To overcome the above limitations, a novel method of hub node identification is proposed. Based on the ridership-weighted network model, the node centrality and reliability are aggregated to quantify the weighted comprehensive importance of the nodes. Furthermore, network invulnerability measurement is used to demonstrate the effectiveness of the proposed method. This method is applied to the Xi'an Urban Rail Transit Network (XURTN) from 2011 to 2021. With the XURTN's development, its connectivity, balance, and fault tolerance have improved. After the basic network skeleton was formed, the number and proportion of hub nodes increased steadily. By comparing the spatial characteristics of the identified hub nodes over two successive periods, it can be found that the evolution direction of the hub nodes is correlated with the type of new lines and coincides also with the development direction of the urban area. In addition, the node orders of the proposed method have a greater impact on the network vulnerability, in which the network-weighted efficiency E-w decreases faster and more dramatically, that is, 1.17%-45.75% more than that of other methods. Overall, this study provides a basis for the URTN and station planning and management.
引用
收藏
页码:549 / 569
页数:21
相关论文
共 50 条
  • [21] Research on Hyperpaths in the Urban Rail Transit Network
    Li, Jinhai
    Liu Jianfeng
    MATERIALS SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY, PTS 1 AND 2, 2014, 488-489 : 1439 - +
  • [22] Robustness analysis of urban rail transit network
    Xu H.
    Li Y.
    International Journal of Performability Engineering, 2019, 15 (10) : 2762 - 2771
  • [23] Research on the evaluation of urban rail transit network
    Zhang, Kai
    Qin, Bin-Bin
    Liu, Yong-Shen
    Zhang, Qiang
    Zhang, K., 1600, Editorial Department of Journal of Railway Engineering Society, China (31): : 97 - 101
  • [24] Understanding Transit Ridership Demand for the Multidestination, Multimodal Transit Network in Atlanta, Georgia: Lessons for Increasing Rail Transit Choice Ridership while Maintaining Transit Dependent Bus Ridership
    Brown, Jeffrey
    Thompson, Gregory
    Bhattacharya, Torscha
    Jaroszynski, Michal
    URBAN STUDIES, 2014, 51 (05) : 938 - 958
  • [25] Vulnerability Analysis of Urban Rail Transit Network considering Cascading Failure Evolution
    Sun, Ranran
    Zhu, Guangyu
    Liu, Bing
    Li, Xiaolu
    Yang, Yiyuan
    Zhang, Jingxuan
    JOURNAL OF ADVANCED TRANSPORTATION, 2022, 2022
  • [26] Vulnerability assessment and evolution analysis of Beijing's Urban Rail Transit Network
    Zhao, Jiaqi
    Liang, Qinghuai
    Guo, Jiaao
    Pu, Keqian
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 653
  • [27] Research on ridership forecast of urban rail transit station based on mixed geographic weighted regression
    Qi, Changlu
    Hu, Hao
    Journal of Railway Science and Engineering, 2021, 18 (07) : 1903 - 1909
  • [28] Bottleneck Identification Method of Urban Rail Transit Network Based on Spectral Clustering
    Zhao, Ruoyu
    Liu, Jun
    2019 4TH INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION (ICECTT 2019), 2019, : 341 - 347
  • [29] The Robustness of Urban Rail Transit Network based on Complex Network Theory
    Gu, Yiran
    Li, Cheng
    PROCEEDINGS OF THE 2016 3RD INTERNATIONAL CONFERENCE ON MATERIALS ENGINEERING, MANUFACTURING TECHNOLOGY AND CONTROL, 2016, 67 : 1068 - 1074
  • [30] Forecasting Method for Urban Rail Transit Ridership at Station Level Using Back Propagation Neural Network (vol 2016, 9527584, 2016)
    Li, Junfang
    Yao, Minfeng
    Fu, Qian
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2017, 2017