Vehicle dynamic states used in various advanced driving safety system are influenced by road geometry. Among the road geometry information, the vehicle pitch angle affected by longitudinal road slope and acceleration-deceleration is essential parameter used in pose estimation with navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the sensor measuring the road slope is not wide used. The digital map including the road geometry data and high-precise positioning system such as DGPS-RTK(Differential Global Positioning System – Real Time Kinematics) are used unusually. In this paper, low cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. Two sequential EKFs measure several vehicle states such as yaw rate, steering angle and velocity, and use nonlinear vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation and T-car experiment


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    Titel :

    Vehicle Dynamics and Road Slope Estimation based on Cascade Extended Kalman Filter


    Beteiligte:
    Kim, Moon-sik (Autor:in) / Kim, Beom-jae (Autor:in) / Kim, Chang-il (Autor:in) / So, Moon-hyung (Autor:in) / Lee, Gwang-soo (Autor:in) / Lim, Jae-hwan (Autor:in)


    Erscheinungsdatum :

    2018-09-01


    Format / Umfang :

    961643 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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