This paper introduces the development of an autonomous driving system in autonomous electric vehicles, which consists of a simplified motion-planning program and a Model-Predictive-Control-Based (MPC-based) control system. The motion-planning system is based on polynomial parameterization, which computes a path toward the expected longitudinal and lateral positions within required time interval in real scenarios. Then the MPC-based control system cooperates the front steering and individual wheel torques to track the planned trajectories, while fulfilling the physical constraints of actuators. The proposed system is evaluated through simulation, using a seven-degrees-offreedom vehicle model with a ‘magic formula’ tire model. The simulations and validation through CarSim show that the proposed planner algorithm and controller are feasible and can achieve requirements of autonomous driving in normal scenarios.


    Access

    Download


    Export, share and cite



    Title :

    Integration of motion planning and model-predictive-control-based control system for autonomous electric vehicles


    Contributors:
    Guodong Yin (author) / Jianghu Li (author) / Xianjian Jin (author) / Chentong Bian (author) / Nan Chen (author)


    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown






    Integration of motion planning and model-predictive-control-based control system for autonomous electric vehicles

    Yin, Guodong / Li, Jianghu / Jin, Xianjian et al. | British Library Online Contents | 2015


    Development of model predictive motion planning and control for autonomous vehicles

    Tosolin, Guido / Cartró, Jaume / Sharma, Vishwas | Springer Verlag | 2019