Obtaining the traffic operation state of the road network can help the traffic management department to optimize management measures, provide reference for travelers on travel modes and travel routes, effectively alleviate the congestion situation and avoid the vicious circle caused by blindly building more roads. Floating car method has become an important method for intelligent transportation system to collect road network operation information, and the collected data has the advantages of large quantity, wide coverage, low cost and great representativeness. This paper starts with GPS data collected by taxis in Dongguan, China, extracts traffic parameters from them, and uses clustering algorithm to identify traffic conditions. Finally, according to the correlation analysis method, the temporal and spatial variation law of the running state of each section in the road network is mined, which provides suggestions for improving traffic conditions.


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    Titel :

    Analysis of urban road network operation state based on GPS data of floating car


    Beteiligte:
    Kong, Xiangjie (Herausgeber:in) / Falcone, Francisco (Herausgeber:in) / Gao, Shangxin (Autor:in)

    Kongress:

    3rd International Conference on Internet of Things and Smart City (IoTSC 2023) ; 2023 ; Chongqing, China


    Erschienen in:

    Proc. SPIE ; 12708


    Erscheinungsdatum :

    14.06.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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