Longitudinal control of autonomous vehicles (AVs) has long been a prominent subject and challenge. A hierarchical longitudinal control system that integrates deep deterministic policy gradient (DDPG) and proportional–integral–derivative (PID) control algorithms was proposed in this paper to ensure safe and efficient vehicle operation. First, a hierarchical control structure was employed to devise the longitudinal control algorithm, utilizing a Carsim-based model of the vehicle’s longitudinal dynamics. Subsequently, an upper controller algorithm was developed, combining DDPG and PID, wherein perceptual information such as leading vehicle speed and distance served as input state for the DDPG algorithm to determine PID parameters and output the desired acceleration of the vehicle. Following this, a lower controller was designed employing a PID-based driving and braking switching strategy. The disparity between the desired and actual accelerations was fed into the PID, which calculated the control acceleration to enact the driving and braking switching strategy. Finally, the effectiveness of the designed control algorithm was validated through simulation scenarios using Carsim and Simulink. Results demonstrate that the longitudinal control method proposed herein adeptly manages vehicle speed and following distance, thus satisfying the safety requirements of AVs.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Longitudinal Hierarchical Control of Autonomous Vehicle Based on Deep Reinforcement Learning and PID Algorithm


    Beteiligte:
    Jialu Ma (Autor:in) / Pingping Zhang (Autor:in) / Yixian Li (Autor:in) / Yuhang Gao (Autor:in) / Jiandong Zhao (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt





    Autonomous Vehicle Driving Path Control with Deep Reinforcement Learning

    Tiong, Teckchai / Saad, Ismail / Teo, Kenneth Tze Kin et al. | IEEE | 2023



    Autonomous vehicle navigation with deep reinforcement learning

    Cabañeros López, Àlex | BASE | 2019

    Freier Zugriff

    Autonomous Vehicle Simulation Using Deep Reinforcement Learning

    Kadam, Rishikesh / Vidhani, Vishakha / Valecha, Bhavika et al. | TIBKAT | 2021