In recent years, the number of motor vehicles in China has continued to grow, making road traffic congestion an increasingly serious problem. The problem of road congestion can no longer be solved by the expansion of roads. Big data technology is becoming increasingly mature, and it brings new ideas to solve the urban traffic problem. This paper is based on the Hadoop platform, through the analysis of path planning algorithms. This paper addresses the shortcomings of current path planning algorithms and improves the A* path planning algorithm. The article obtains real-time shortest paths based on the path planning of the improved A* algorithm, verifies them by example, and compares and analyses them with the traditional shortest path algorithm. The experimental results demonstrate the effectiveness of the algorithm in different traffic flow states.


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    Titel :

    Research on Urban Traffic Route Planning Based on Big Data


    Beteiligte:
    Liu, Honggang (Autor:in) / Li, Fang (Autor:in) / Zhang, Tianrang (Autor:in)


    Erscheinungsdatum :

    15.04.2022


    Format / Umfang :

    1769862 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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