Distributed Model Predictive Platooning Control of Heterogenous CAVs Under Markovian Switching Communication Topologies

This paper considers the platooning control problem of heterogenous connected and automated vehicles (CAVs) under switching communication topologies. We propose a distributed model predictive control (DMPC) strategy for platooning control of the nonlinear CAVs constrained by speed and torque. The communication topologies of the platoon are characterized as the Markov chain of a set of randomly switched directed graphs. Then the neighbors' state information and the time-dependent graph function are used to formulate the control goals. By minimizing the objective function, the Markovian swithched DMPC algorithm of the platoon is presented. Moreover, some sufficient conditions are derived to ensure the vehicle platooning system's stability and string stability. Some typical traffic scenarios are used to verify and evaluate the performance of the DMPC strategy proposed in this paper.