A Cooperative Lane Change Control Strategy for Connected and Automated Vehicles by Considering Preceding Vehicle Switching

The cooperative lane change among several connected and automated vehicles (CAVs) provides ideas for enhancing the traffic safety and efficiency issues caused by lane changes. However, most of the existing studies mainly focus on the independent analysis of the lateral and longitudinal movements of the lane change without considering the impact of the lateral motion on the longitudinal motion. These works usually assume that the target tracking-preceding vehicles are determined for both the lane change vehicle and the following cooperative vehicle in the target lane. This work proposes a model predictive control (MPC)-based cooperative lane change (CLC) control strategy by considering the preceding vehicle switching and the correlation between the lateral and longitudinal motions. It builds the lateral movement based on the appropriate function curve and integrates this lateral movement in the construction of the coordinated longitudinal motion control strategy by using a set of linear piecewise functions in the design of constraints and objective function of the optimization model to provide smooth preceding vehicles switch. An advanced optimization solver is used to solve the optimization control problem step by step. The proposed strategy is validated based on numerical comparative experiments with two typical lane-changing scenarios. The results show that the proposed control strategy can smoothly complete the preceding vehicle switching during the lane change and quickly realize the stable tracking of the target lane vehicles after changing lanes.