Urban road traffic key nodes have a great influence on the urban road traffic, traffic state key nodes will also affect the adjacent nodes, thus a greater influence on road network, the information entropy can characterize degree of chaos system, this article through to acquisition of various lane traffic tunnel section, the information entropy to calculate the key nodes, Then, node information entropy is used to represent the degree of traffic congestion in urban tunnel sections. Finally, statistical analysis is conducted to find the change law of information entropy at the intersection entry point and the entrance information entropy at the tunnel exit.


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    Title :

    Traffic congestion recognition based on information entropy


    Contributors:
    Guo, Chenxing (author) / Zhang, Juan (author) / Cao, Zhen (author)

    Conference:

    International Conference on Smart Transportation and City Engineering 2021 ; 2021 ; Chongqing,China


    Published in:

    Proc. SPIE ; 12050


    Publication date :

    2021-11-10





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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