This study applies complex network theory to analyze the structure and robustness of Gansu Province's highway, railway, civil aviation, and integrated passenger transportation networks. The aim is to enhance the robustness of the province's transportation system for stable and efficient operation. It constructs the highway, railway, and civil aviation subnetworks using the Space P method and combines nodes at the county level to form the integrated passenger transportation network. Then, it analyzes the structures of these networks based on node and network characteristics. Finally, it simulates various attack strategies to assess network robustness and pinpoint critical nodes. The results indicate: (1) In terms of network structure, the highway, railway passenger transportation subnetworks, and the integrated passenger transportation network in Gansu Province exhibit clear small-world characteristics, displaying a "radiating" network structure. In contrast, the civil aviation subnetwork adopts a single-centered "star" structure. (2) Nodes with higher centrality in the passenger transportation network have lower clustering coefficients. (3) In terms of network comparison, the robustness of the networks ranks as follows: composite passenger transportation network > highway passenger transportation subnetwork > railway passenger transportation subnetwork > civil aviation passenger transportation subnetwork. (4) Regarding the effectiveness of robustness attacks, closeness attack outperforms the other three attack methods. Thus, from the perspective of closeness centrality, key hub nodes in Gansu Province's passenger transportation network include cities such as Lanzhou, Tianshui, Dingxi, Longnan, and Longxi County.


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    Title :

    Research on the structure and robustness of multimodal composite passenger transport networks in Gansu province


    Contributors:

    Conference:

    International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China


    Published in:

    Proc. SPIE ; 13575 ; 135752L


    Publication date :

    2025-04-28





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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