An optimized scheduling method with dynamic conflict graph for connected and automated vehicles at multi-lane on-ramp areas

The on-ramp merging is one of the typical bottlenecks on highways, and it’s expected to improve vehicle safety and traffic efficiency in this area through multi-vehicle collaboration. Existing research rarely coordinates on-ramp merging utilizing global information in a cyber-physical system, and most of them assume that vehicles in the mainline wouldn’t change lanes for simplification. However, scheduling methods dealing with multi-lane merging areas have been less explored. To address the problem, an optimized scheduling method with dynamic conflict graph is proposed in this study. First, the dynamic conflict graph is established, where vertices define the attributes of vehicle groups and edges describe the relationship among them; the optimization problem is then reconstructed as a graph search problem. Subsequently, a graph decomposition method is presented for the dynamic conflict graph. The feasible domain of vertices’ final states and costs of edges are determined based on optimal control theory, after which the heuristic depth-first search strategy is adopted to find a near-optimal solution. Finally, the dynamic conflict graph is applied in a continuous traffic flow. Simulations are conducted, and the performance is compared with the default algorithm in SUMO. The simulation results reveal that the proposed method reduces the overall travel delay while guaranteeing safety.