A dual-layer collaborative control method for signal timing and mixed-vehicle platoons at intersections in intelligent transportation systems

In intelligent transportation systems, connected and automated vehicles (CAVs) provide enhanced connectivity, observability, and controllability, creating new opportunities for coordinated intersection control. However, in mixed traffic environments consisting of CAVs and human-driven vehicles (HVs), the stochastic behaviors and uncertainties of HVs can undermine these potential benefits. To address this issue, this study proposes a dual-layer collaborative control method for jointly optimizing signal timing and mixed-vehicle platoons at intersections. In the upper layer, dynamic vehicle splitting and merging are employed to form CAV-led mixed platoons, while signal timing and the desired arrival times of the platoons are jointly optimized to improve traffic efficiency and computational efficiency. In the lower layer, CAV trajectories are optimized using an analytical optimal control solution that considers both energy consumption and driving comfort. A rolling optimization mechanism is further incorporated to enhance stability and real-time adaptability. Simulation results show that, compared with Actuated Signal Control and Optimization-based Traffic Signal Control, the proposed method significantly reduces average delay and fuel consumption under various traffic demands and CAV penetration rates. It also improves driving comfort and reduces computation time by approximately one order of magnitude. These findings demonstrate the potential of the proposed method for real-time intersection control in intelligent transportation systems.