Driving on bumpy roads with potholes or bulges may severely compromise vehicle ride comfort, while in extreme cases safety may be affected. Existing approaches mainly focus on suspension control to ease the discomfort by adjusting equiv-alent damping and stiffness or exerting active forces to ease the ride. In conventional approaches, these adjustments need to know the irregular input information of road ahead via camera or lidar sensors. In car following scenarios, it is difficult to directly get such information, since a pothole may be occluded by preceding vehicles. This work proposes an alternative way to alleviate passenger discomfort by proactively estimating the road irregularity based on preceding vehicle responses, and then by optimizing the timing of road irregularity excitation in speed planning, the weighted discomfort index is reduced. First, a Kalman filter with general knowledge of vehicle suspension dynamics is designed, which can output pothole distribution results according to the vertical responses of preceding vehicle body. Then, considering the sensitive frequency band of pas-senger, a motion planning algorithm is proposed to optimize the frequency-weighted acceleration when passing the road irregularity. Compared with a typical car following model IIDM-CAH, the proposed algorithm shows effective mitigation of discomfort caused by the road irregularities, while not sacrificing safety performances. This approach may be applied in automated vehicles, and may also work together with active suspension control to achieve better improvement in passenger comfort.


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    Titel :

    Safe and Comfortable Motion Planning for Bumpy Road Driving


    Beteiligte:
    Zhang, Jiajie (Autor:in) / Xiao, Bin (Autor:in) / Tang, Binbin (Autor:in) / Jiang, Yangye (Autor:in) / Yu, Tingzhe (Autor:in) / Li, Daofei (Autor:in)


    Erscheinungsdatum :

    24.09.2023


    Format / Umfang :

    1147881 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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