Distributed Drive Autonomous Vehicle Trajectory Tracking Control Based on Multi-Agent Deep Reinforcement Learning

In order to enhance the trajectory tracking accuracy of distributed-driven intelligent vehicles, this paper formulates the tasks of torque output control for longitudinal dynamics and steering angle output control for lateral dynamics as Markov decision processes. To dissect the requirements of acti...

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Bibliographic Details
Published in:	Mathematics (Basel) Vol. 12; no. 11; p. 1614
Main Authors:	Liu, Yalei, Ding, Weiping, Yang, Mingliang, Zhu, Honglin, Liu, Liyuan, Jin, Tianshi
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2024
Subjects:	Algorithms Autonomous vehicles Control algorithms Control methods Control systems Controllers Decision making deep deterministic policy gradient Deep learning deep Q-network Deviation distributed drive autonomous vehicles Driverless cars Efficiency Equipment and supplies Intelligent vehicles Kinematics Lateral control Markov processes Methods Motion control multi-agent deep reinforcement learning Multiagent systems Neural networks Steering Tracking control Trajectory control trajectory tracking China
ISSN:	2227-7390, 2227-7390
Online Access:	Get full text
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