The present disclosure provides a method for managing traffic congestion in a smart city. The method includes predicting, based on a trained traffic state prediction model, one or more target areas where the traffic congestion is likely to occur from the preset area during a next time period by processing the traffic data information during the current time period, the traffic state prediction model being a Graph Neural Network (GNN) model and a predicted result being output by at least one node of a traffic state prediction model; determining whether a traffic scheduling strategy is needed to be switched based on traffic data information in the one or more target areas during the next time period; and in response to determining that the traffic scheduling strategy is needed to be switched, switching a first traffic scheduling strategy to a second traffic scheduling strategy.


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    Title :

    METHODS FOR MANAGING TRAFFIC CONGESTION IN SMART CITIES AND INTERNET OF THINGS (IOT) SYSTEMS THEREOF


    Contributors:
    SHAO ZEHUA (author) / LI YONG (author) / QUAN YAQIANG (author) / LIU BIN (author) / WEN ZHIHUI (author)

    Publication date :

    2023-04-20


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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