Dynamic Space-time Resource Allocation for Signal-less Intersection Management in a Connected Autonomous Vehicle Environment

In this paper, we consider the problem of dynamic space-time resource allocation for optimizing the movements of connected autonomous vehicles (CAVs) through intersections without traffic signals. We design a three-dimensional (3D) space-time resource model for maintaining the intersection resource information in both the two-dimensional (2D) space domain and the time domain. In the 3D resource model, the trajectory of a CAV through an intersection is assigned a specific parallelepiped resource that spans both 2D space and time domains. Moreover, the dynamic space-time resource allocation problem is simplified to a classic 3D container-packing problem. We propose a dynamic heuristic algorithm, Best Parallelepiped Fit (BPF), to maintain smooth traffic flow and maximize spacetime resource usage by adjusting the speed and entry time of each approaching CAV through intersections. We evaluate the performance of the proposed algorithm under different traffic loads, and simulation results indicate that our algorithm can greatly reduce the average travel delay of CAVs.