Nash optimality based distributed model predictive control for vehicle platoon

In this paper, a distributed model predictive control algorithm (DMPC) based on Nash optimality is proposed for automated vehicle platoon control. The optimization decision of vehicle platoon is decomposed into the decentralized optimization of single vehicles, in which the Nash optimality algorithm is adopted to solve the decentralized optimization problem. Thus, each vehicle can reach the local optimal target and the whole team can reach its Nash equilibrium. The methodology employs neighborhood information of the entire platoon through on-board sensors and V2V communication to achieve coordination of the entire platoon. The ability of the methods in terms of robustness to disturbances and cyber-physical interaction is demonstrated with simulation case studies. Copyright (C) 2020 The Authors.