Temporal-spatial dimension extension-based intersection control formulation for connected and autonomous vehicle systems

Abstract Traffic congestion has become a serious issue worldwide due to the rapid increase in population and traffic demands. Advances in connected automated vehicle (CAV) technology demonstrate the potential to improve traffic mobility and safety performance at intersections. An advanced intersection control system is proposed in this study to coordinate vehicle trajectories and ensure safety and operation efficiency at intersections. A temporal-spatial dimension extension-based trajectory coordination model is developed by formulating all possible trajectories of vehicles at the intersection. Correspondingly, according to the trajectory coordination model, two signal-free control algorithms, including the priority-based algorithm and the Discrete Forward-Rolling Optimal Control (DFROC) algorithm are proposed in this study to manage vehicles at the intersection. These two algorithms, together with the FCFS policy, are compared with the conventional signal control method in a SUMO-based simulation platform. Experimental results indicate that the proposed algorithms outperform the signal control method in terms of reducing total traffic delays at intersections and increasing intersection capacity and operation efficiency.