In the hierarchical composite highway environment, anomalies such as misidentification and reverse identification may occur between ETC gantry antennas and onboard media, leading to confusion in stored path and billing information within onboard media, causing abnormalities in toll collection at exits. To achieve precise identification of vehicles in both upper and lower layers, a multi-level data fusion-based hierarchical vehicle identification method is proposed. The basic idea is to utilize front-end perception devices such as ETC positioning antennas, LiDARs, video cameras, and license plate recognition camera. The target positioning information formed by the fusion of LiDARs and video cameras is fused with the target positioning information identified by ETC positioning antennas and gantry cameras, the identification information of successfully matched vehicles is extracted from the transaction records of ETC positioning antennas to obtain accurate vehicle perception data. The identification information is written into onboard media through ETC positioning antennas, achieving precise matching of driving vehicles and onboard media at the front end, forming complete structured vehicle information and unstructured vehicle images to support hierarchical and precise vehicle identification. The accuracy of the algorithm was validated through the development and testing of a prototype system.


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    Title :

    Hierarchical Composite Highway Vehicle Precise Identification Based on Multi-Source Data Fusion


    Additional title:

    Advances in Engineering res


    Contributors:

    Conference:

    International Symposium on Traffic Transportation and Civil Architecture ; 2024 ; Tianjin, China June 21, 2024 - June 23, 2024



    Publication date :

    2024-09-24


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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