A Dynamic Control Method for Cavs Platoon Based on the MPC Framework and Safety Potential Field Model

摘要

Safety and efficiency have always been significant challenges to the development of road traffic. Detailed vehicle motion information is the prerequisite for achieving optimal control of the platoon and improving traffic safety and efficiency. The connected and automated vehicles (CAVs) system has offered unprecedented opportunities for the real-time collection and processing of these detailed vehicle motion data. Based on the model predictive control (MPC) framework and safety potential field (SPF) model, we developed an alternative CAVs platoon dynamic control method. The SPF model was applied to describe the road risk distribution under the complex driving environment and was embedded in the MPC framework to optimize the vehicle dynamics from the perspective of capacity, safety, and energy-saving. Also, some experiments were performed to verify the validity of our platoon control strategy. Compared with the fixed time-headway strategy, our proposed strategy can increase the traffic capacity by about 24.4%, while ensuring safety and improving fuel economy. The results indicate that the novel CAVs platoon control methodology proposed in this paper can be potentially applied to alleviate various traffic problems (e.g., traffic congestion, traffic accidents, and high emissions).