Distributed Model Predictive Control for Two-Dimensional Electric Vehicle Platoon Based on QMIX Algorithm

Abstract

In this paper, an improved distributed model predictive control (IDMPC) method for the platoon consisting of electric vehicles is put forward. And the motion of the platoon is performed in two dimensions, which contains longitudinal motion and lateral motion. Firstly, a platoon model is built based on the car-following model for a single following vehicle. Then, the IDMPC strategy is designed with the consideration of multiple objectives. The symmetrical weight matrices in the IDMPC are important for the final control effect. To control each following vehicle in the platoon coordinately, the weights for the IDMPC are optimized based on the QMIX algorithm in multi-agent reinforcement learning. The QMIX can fully consider the global information in the multi-vehicle following process; therefore, the IDMPC can get optimal control variables. Finally, the simulation and experimental results verify the IDMPC. Compared to the comparison strategies, the IDMPC has the better lane tracking, stability in lateral direction and economic performance.

Keywords

• electric vehicle
• platoon control
• distributed model predictive control
• weights
• QMIX