In order to match the vehicle travel path accurately and completely on an urban road network, reproduce the travel pattern of vehicles, and provide data support for analyzing the temporal and spatial distribution characteristics of urban traffic, this paper proposed a vehicle travel path matching algorithm based on license plate recognition data. First, the travel chain was extracted by license plate classification and timestamp sorting. Second, the single trip of vehicle was separated by threshold control. Then, the path selecting probability was calculated based on the K shortest paths (KSP) algorithm and the path selection probability function based on the Logit model. Finally, the missing path was completed in combination with the entrance direction. Taking the license plate recognition data of a region in Shandong Province as an example, the algorithm proposed in this paper is compared with other algorithms to verify the validity of the algorithm by flow distribution.


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    Titel :

    Vehicle Travel Path Matching Algorithm Based on License Plate Recognition Data


    Beteiligte:
    Wang, Yu (Autor:in) / Wang, Lei (Autor:in) / Gu, Xinxin (Autor:in) / Wang, Jiangfeng (Autor:in)

    Kongress:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Erschienen in:

    CICTP 2022 ; 3060-3070


    Erscheinungsdatum :

    2022-09-08




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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