Traffic strategy of signalized intersection integrating vehicle lane change and velocity trajectory optimization in mixed traffic environment

With the rapid advancement of autonomous driving and communication technologies, connected and automated vehicles (CAVs) offer new opportunities to enhance the efficiency of road operations at urban intersections. However, most existing studies assume full vehicle-to-everything (V2X) connectivity, and their control strategies often address lateral (e.g., lane-changing) and longitudinal (e.g., trajectory) control separately. To address these limitations, this paper proposes an integrated strategy for joint optimization of lane-changing and velocity trajectory planning at signalized intersections within a mixed-traffic environment involving diverse vehicle types. Specifically, the approach targets two key issues: right-turn blocking caused by straight-moving vehicles in shared straight-right lanes, and stop-and-go inefficiencies in straight-through lanes. Using a two-layer framework, we strategically manage a minimal number of CAVs—first determining optimal passage strategies based on real-time vehicle kinematics (including position, velocity, and acceleration) and traffic signal timing, and then generating eco-friendly trajectories that jointly optimize efficiency, ride comfort, and fuel economy. Simulation results demonstrate significant improvements in intersection throughput without compromising fuel efficiency.