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 [Formula: see text] 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.


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    Titel :

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


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Tian, Tian (Autor:in) / Cheng, Yanqiu (Autor:in) / Liang, Yichen (Autor:in) / Ma, Chen (Autor:in) / Chen, Kuanmin (Autor:in) / Hu, Xianbiao (Autor:in)


    Erscheinungsdatum :

    2024-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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