Distributed Model Predictive Control for Heterogeneous Vehicle Platoon With Inter-Vehicular Spacing Constraints

• Published in: IEEE transactions on intelligent transportation systems Vol. 24; no. 3; pp. 1 - 13
• Main Authors: Qiang, Zhiwen, Dai, Li, Chen, Boli, Xia, Yuanqing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic stability; Collision avoidance; Computer networks; coupled constraints; distributed control; Distributed processing; heterogenous platoon control; Iterative methods; Linear matrix inequalities; Local optimization; Model predictive control; Numerical stability; Predictive control; Road transportation; Trajectories; Trajectory; Vehicle dynamics; Vehicles
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2022.3227465

This paper proposes a distributed control scheme for a platoon of heterogeneous vehicles based on the mechanism of model predictive control (MPC). The platoon composes of a group of vehicles interacting with each other via inter-vehicular spacing constraints, to avoid collision and reduce communication latency, and aims to make multiple vehicles driving on the same lane safely with a close range and the same velocity. Each vehicle is subject to both state constraints and input constraints, communicates only with neighboring vehicles, and may not know a priori desired setpoint. We divide the computation of control inputs into several local optimization problems based on each vehicle's local information. To compute the control input of each vehicle based on local information, a distributed computing method must be adopted and thus the coupled constraint is required to be decoupled. This is achieved by introducing the reference state trajectories from neighboring vehicles for each vehicle and by employing the interactive structure of computing local problems of vehicles with odd indices and even indices. It is shown that the feasibility of MPC optimization problems is achieved at all time steps based on tailored terminal inequality constraints, and the asymptotic stability of each vehicle to the desired trajectory is guaranteed even under a single iteration between vehicles at each time. Finally, a comparison simulation is conducted to demonstrate the effectiveness of the proposed distributed MPC method for heterogeneous vehicle control with respect to normal and extreme scenarios.