A Review of Dynamic Lane Assignment with Signal Optimization for Connected Autonomous Vehicles

Abstract: Traffic demand varies significantly in urban areas, impacting intersection performance. Current control strategies assume fixed lane assignment with signal optimization focused on the traffic movements at each approach, leading to inefficient use of temporal and spatial resources. To improve the intersection performance in such cases, Dynamic Lane Assignment (DLA), a component of Intelligent Transportation Systems (ITS), is employed to improve the intersection efficiency. As we move into an era where Connected and Automated Vehicle (CAV) technology is increasingly recognized for enhancing traffic safety and efficiency, it’s important to consider that CAVs and human driven vehicle (HDVs) will co-exist in the system for a substantial period. This necessitates managing CAVs alongside HDVs, which could benefit from dedicated lane assignments for CAVs in conjunction with signal optimization to enhance overall system performance and efficiency. However, research on CAV-based DLA combined with signal optimization in mixed traffic environments remains limited. This research focuses on understanding the state-of-the-art of managing intersections with DLA in mixed traffic environments. Information was gathered from previous research papers, public documents, and other sources. For the synthesis, studies were categorized into the following topics: i) Application of DLA for intersections with CAVs, ii) signal optimization plans for CAVs, iii) Application of DLA combined with signal optimization for CAVs and iv) Application of DLA with signal optimization plan for regular traffic; and v) other lane assignment strategies such as Dynamic Lane Grouping (DLG) and Lane Reversal. The synthesis focuses on the assumptions, strategies, and policies related to lane assignment, as well as the methodologies employed in these studies. Finally, a comprehensive overview of DLA strategies for intersection management with CAV penetration, research gaps, and future directions for DLA and intersection control strategies for mixed traffic environments will be discussed.