Distributed Cooperative Control and Optimization of Connected Automated Vehicles Platoon Against Cut-in Behaviors of Social Drivers

This article proposes a dynamic platoon management and cooperative driving framework for a mixed traffic flow consisting of multiple connected automated vehicles(CAVs) and possible human-driven vehicles(HDVs) that can be regarded as the surrounding vehicles(SVs). Specifically, the proposed framework consists of three stages. At the first stage, the cruising information of all the SVs will be collected by the leader CAV through the Cellular-Vehicle-to-X(C-V2X) infrastructure, while an automatic decision-making driving assistance system(ADMDSS) is constructed to determine the driving states of the platoon. When the HDVs approach the communication range of the platoon, in the second stage, the trajectories of the HDVs will be estimated and the reference trajectory planning for the leader CAV and the cooperative controller design for the follower CAVs will be activated, respectively, by using C-V2X infrastructure. We consider two types of social driving behaviors(SDBs): courteous and rude, where the optimal trajectory estimation for the SDBs will be obtained by the known social preferences of the SVs. While the HDVs enable to impose their social cut-in intentions(SCIIs) into the platoon, the ADMDSS will provide a high-level driving guidance to the platoon to adjust the time-varying space error among the CAVs rejecting the potential cut-in behaviors(CIBs). For this case, the problems of collision avoidance, energy efficiency, and stability of the platoon will be solved at the third stage within a finite time by designing a cooperative trajectory tracking optimization algorithm. Simulation cases are presented to illustrate the effectiveness of the proposed approaches.