A sideslip angle estimation algorithm based on DGPS in V2I cooperative system is proposed. The vehicle kinematic model is built to estimate vehicle yaw angle and sideslip angle; meanwhile, a two-order kalman filter is used to fuse information from different sources. The first-order kalman filter is available for processing lateral acceleration, longitudinal acceleration and yaw rate collected by inertia measurement unit (IMU). This information is used as the time update of vehicle model. The second-order kalman filter is utilized to fuse vehicle location heading angles which are collected by DGPS in cooperative system. This information is used as the measurement update of vehicle model. Steady-state cornering test results show that the algorithm is effective, even if the vehicle is in high lateral acceleration. The algorithm suits vehicle safety control requirements in a V2I-cooperative system.


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    Titel :

    DGPS-Based Vehicle State Estimation in V2I Cooperative System


    Beteiligte:
    Xie, Boyuan (Autor:in) / Zheng, Sifa (Autor:in) / Qin, Xiaohui (Autor:in) / Zhou, Xijun (Autor:in)

    Kongress:

    Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China


    Erschienen in:

    ICTIS 2013 ; 23-32


    Erscheinungsdatum :

    2013-06-11




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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