CIDC: A Flexible Formation Control Framework for Intelligent Connected Vehicles

Intelligent connected vehicles integrate smart systems and network communication to enhance safety and efficiency, making them widely applicable for formation control in diverse scenarios. Current mainstream methods typically split formation control tasks into independent functional modules and establish relationships for transmitting information, which results in a fixed number of vehicles in the fleet and limited flexibility in formation configurations. In this paper, we propose a cooperative integrated decision and control (CIDC) framework for formation control in diverse scenarios. This framework splits the driving task into three modules: static trajectory planning, order allocation, and dynamic optimal tracking. First, in the static trajectory planning module, static traffic elements are considered to generate a set of candidate trajectories, freeing up higher-level constraints and enhancing trajectory planning efficiency. Second, in the order allocation module, reasonable and safety preceding vehicles for following are selected, determining the configuration of the connected vehicle fleet in real-time. Finally, in the dynamic optimal tracking module, a multi-objective optimal tracking problem is designed to track the optimal path while considering dynamic obstacles, thereby improving vehicle autonomy and achieving cooperative formation control with variable vehicle numbers and flexible formation configurations. Simulation and real vehicle experiment results demonstrate that the proposed CIDC framework can achieve automatic formation adjustment, making it suitable for various formation control tasks such as convoy driving, deliver and platoon driving