In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering. From the results we could see the change of vehicle speed depends largely on the traffic environment at the driver’s preview point. On this basis, a novel velocity planner is proposed. Firstly, a target velocity in preview terminal point is calculated. The calculation of the velocity is based on two indicators-the driver’s driving & operating ability, and the degree of visual restriction. The former refers to the ability of the driver to maintain the driveway as well as the control ability of the vehicle stability, and the latter is related to the uncertainty of the environment. Subsequently, the smooth velocity profiles that connect the initial point and the preview terminal point are generated based on the convex optimization. Finally, the simulation results show that this velocity planner possesses good human-like performance, considering the human-vehicle-road coordination. This study is useful to customize velocity planning for autonomous vehicle so as to improve the acceptability of the specific human driver.


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    Titel :

    A Novel Velocity Planner for Autonomous Vehicle Considering Human Driver’s Habits


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Pei, Xiaofei (Autor:in) / Guo, Xuexun (Autor:in) / Cui, Zongwei (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2020



    Erscheinungsdatum :

    2020-04-14




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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