Real-Time Priority-Based Cooperative Highway Merging for Heterogeneous Autonomous Traffic

Highway on-ramp merge junctions remain a major bottleneck in transportation networks. However, with the introduction of Connected Autonomous Vehicles (CAVs) with advanced sensing and communication capabilities modern algorithms can capitalize on the cooperation between vehicles. This paper enhances highway merging efficiency by optimally coordinating CAVs in order to maximize the flow of vehicles while satisfying all safety constraints. Focus is also placed on the effect of varying priorities of different vehicle classes in selecting the best merging sequence. Our algorithm is capable of real time operation through parallel computation, optimized merge sequence generation and management of the diverse needs of heterogeneous (multi-class) traffic. Results are verified through a realistic traffic simulation software.