Intelligent control of autonomous vehicles has been an important research topic due to the model uncertainties and complexities of vehicle dynamics. In this paper, we proposed an approximate dynamic programming (ADP) approach for path following control of an autonomous vehicle. The idea is to use the Dual Heuristic Programming (DHP) algorithm, which is an efficient class of ADP methods, to directly control the steer angle of the vehicle's wheels. In order to perform data-driven simulation studies, we established the kinematic model of the vehicle and the model of the steering wheels. Then, the DHP algorithm was designed for path following control by using a Markov decision process model. Simulation results illustrated that the proposed method can achieve good performance for the path following control problem.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An approximate dynamic programming approach for path following control of an autonomous vehicle


    Beteiligte:
    Kun Zhao (Autor:in) / Jian Wang (Autor:in) / Xin Xu (Autor:in) / Zhenhua Huang (Autor:in)


    Erscheinungsdatum :

    01.06.2014


    Format / Umfang :

    1099936 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Kernel-based Approximate Dynamic Programming for Autonomous Vehicle Stability Control

    Guo, Hongyan / Tan, Zhongqiu / Liu, Jun et al. | IEEE | 2022


    Autonomous Vehicle Path Tracking Control based on Adaptive Dynamic Programming

    Guo, Hongyan / Li, Guangyao / Liu, Jun et al. | IEEE | 2023




    Adaptive Dynamic Preview Control for Autonomous Vehicle Trajectory Following with DDP Based Path Planner

    Wu, Ning / Huang, Weiwei / Wu, Xiaojun et al. | British Library Conference Proceedings | 2015