This paper presents the design and implementation of an intelligent switched control for lateral control of autonomous vehicles. The switched control is designed based on Linear Parameter-Varying (LPV) and Youla-Kucera (YK) parameterization. The proposed intelligent system aims to optimize the control switching performance using a Reinforcement Learning (RL) model. The presented approach studies the critical problem of initial or sudden large lateral errors in lane-tracking or lane-changing. It ensures stable and smooth switching performance to provide a smooth vehicle response regardless of the lateral error. The proposed RL-based switching strategy is validated using a RENAULT simulator on MATLAB, and compared to another modeled switching strategy with encouraging results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Intelligent Control Switching for Autonomous Vehicles based on Reinforcement Learning*


    Beteiligte:


    Erscheinungsdatum :

    05.06.2022


    Format / Umfang :

    1587014 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Reinforcement Learning-Based Predictive Control for Autonomous Electrified Vehicles

    Liu, Teng / Yang, Chao / Hu, Chuanzheng et al. | IEEE | 2018


    REINFORCEMENT LEARNING-BASED PREDICTIVE CONTROL FOR AUTONOMOUS ELECTRIFIED VEHICLES

    Liu, Teng / Yang, Chao / Hu, Chuanzheng et al. | British Library Conference Proceedings | 2018



    Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routing

    Mushtaq, Anum / Haq, Irfan ul / Sarwar, Muhammad Azeem et al. | ArXiv | 2022

    Freier Zugriff

    Bilateral Control Model for Autonomous Vehicles Based on Deep Reinforcement Learning

    Liu, Kan / Jiao, Pengpeng / Hong, Weiqi et al. | IEEE | 2025