In advanced driver assistance systems (ADAS) or autonomous driving Systems (ADS) the robust and reliable perception of the environment, especially for the detecting and tracking the surrounding vehicle is prerequisite for collision warning and collision avoidance. In this paper a post-fusion tracking approach is presented which combines the front view Radar observation and front smart camera information. The approach can improve the tracking accuracy of the tracking system to support ADAS or ADS function such as adaptive cruise control (ACC) or autonomous emergency braking (AEB). The paper describes the state estimation algorithm, data association in the fusion architecture. Furthermore, the fusion architecture is tested and validated in real highway driving scenario.


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    Titel :

    Radar and Smart Camera Based Data Fusion for Multiple Vehicle Tracking System in Autonomous Driving


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Li, Fu-Xiang (Autor:in) / Lu, Ke (Autor:in) / Zhu, Yuan (Autor:in) / Wu, Zhihong (Autor:in)

    Kongress:

    SAE 2021 Intelligent and Connected Vehicles Symposium Part II ; 2021



    Erscheinungsdatum :

    31.03.2022




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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