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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:
    Kun Zhao (author) / Jian Wang (author) / Xin Xu (author) / Zhenhua Huang (author)


    Publication date :

    2014-06-01


    Size :

    1099936 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    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