Autodriver algorithm aims to develop a path-following algorithm for autonomous vehicles using road geometry data and vehicle dynamics. In this study, a novel smart Autodriver algorithm is developed according to practical implications utilizing a more realistic vehicle model and consideration of real-time applicability. A ghost-car path-following approach is introduced to define the desired location of the vehicle at every instance during various maneuvers. Key steady-state characteristics of turning vehicles, namely the curvature, yaw rate, and side-slip responses are discussed and used to construct a path-following controller based on the Autodriver algorithm. A feedback control based on Sliding Mode Control (SMC) is also designed and applied to minimize transient errors between the road and the vehicle positions. Finally, simulations are performed to analyze the path-following performance of the proposed scheme compared to a Model Predictive Controller (MPC) as a widely accepted popular method for autonomous vehicles. Hardware-in-the-loop (HIL) tests are also performed to investigate real-time applicability of the controllers. The results show promising controller performance in terms of error minimization, passenger comfort, and low computational cost for the proposed method.


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    Titel :

    Smart Autodriver Algorithm for Real-Time Autonomous Vehicle Trajectory Control


    Beteiligte:
    Milani, Sina (Autor:in) / Khayyam, Hamid (Autor:in) / Marzbani, Hormoz (Autor:in) / Melek, William (Autor:in) / Azad, Nasser L. (Autor:in) / Jazar, Reza N. (Autor:in)


    Erscheinungsdatum :

    01.03.2022


    Format / Umfang :

    5121774 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch