Multi-Vehicle Collaborative Trajectory Planning for Emergency Vehicle Priority at Autonomous Intersections

Abstract

Emergency vehicle (EV) prioritization plays an important role in improving rescue efficiency and saving lives and property. Most existing studies have been confined to either investigating signal prioritization for EVs at intersections or focusing on clearing emergency lanes on road segments, with limited consideration for an integrated approach that combines both methods. In this study, we have developed a bi-level trajectory planning model aimed at optimizing the trajectories of EVs at intersections and road segments located within the communication range, using vehicle-to-everything technology. The upper-level model is designed to plan the entry times, speeds, and internal trajectories of vehicles within the intersection while avoiding any conflicts that may arise during their movements. In particular, to address the dimensionality of the proposed large-scale optimization problems, we introduce the equidistant discretization method to discretize the entry speeds of vehicles into a finite set of selectable values. The lower-level model focuses on optimizing the longitudinal and lateral trajectories on roadways to ensure that vehicles arrive at the stop line punctually and promptly. Both the upper- and lower-level models are formulated as mixed-integer linear programming models. The A Mathematical Programming Language and the Gurobi solver are employed for optimization. The case study demonstrates that the proposed model effectively optimizes vehicle trajectories at intersections and road segments, leading to a significant reduction in delays for EVs.