Key nodes play a vital role in the transportation network by significantly influencing its structure, function, and reliability. Their failure can severely limit the transportation efficiency and passenger flow of urban agglomerations. To address the limitations of single traffic mode and incomplete evaluation indexes, this paper proposes a weighted multi-layer network node importance evaluation method that considers node connectivity, diverse transportation modes, and service capabilities (CDSM). Firstly, based on the long-distance bus stations, railway stations, and airports in the Beijing-Tianjin-Hebei urban agglomeration (BTHUA), the comprehensive transportation network (CTN) is constructed. Secondly, evaluation indexes including degree, closeness, capacity, and grade are selected to build the weighted model and obtain the comprehensive importance of nodes. Finally, the effectiveness of the method is verified by the susceptible-infected-recovered model. The results show that: 1) The CTN in this paper can reflect real traffic links among different transportation modes in urban agglomerations. 2) When the top 5 and top 10 key nodes identified by the CDSM are used as initial infected nodes, the infection and propagation rate of the CTN are higher than traditional methods such as the using degree, betweenness, closeness, and k-shell. Specifically, the infection rate is 2.8% and 3.2% higher than the average of these methods, and the propagation rate is 7 and 2.3 time steps faster respectively. 3) The more key nodes initially infected, the higher the infection and propagation rate of the CTN. 4) The key nodes identified in this paper include important transportation hubs of BTHUA, aligned with reality.


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    Title :

    Identification of Key Nodes in Comprehensive Transportation Network: A Case Study in Beijing-Tianjin-Hebei Urban Agglomeration, China


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Zhang, Ye (author) / Zheng, Shuyan (author) / Chen, Yanyan (author)


    Publication date :

    2023-08-08




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English