Coordination of Signal and Vehicle Trajectory at Intersections for Mixed Traffic Flow

The intersection traffic control under the mixed traffic environment can be realized by the coordination of the signal control and the trajectory control of automated vehicles, which can greatly improve the utilization efficiency of road traffic resources. The centralized control strategies in previous studies with the integrated optimization of signal timing and vehicle trajectory are difficult to be applied to the real operations with self-organized vehicles, and often have high computational complexity. In this paper, a logic-based coordinated control of the signal and vehicle trajectory is proposed within a decentralized framework. Based on the active servo control principle of fast and slow variables in the coordination theory, a coordination framework of the slow variables of intersection signal timing and the fast variables of vehicle trajectory strategy is designed. A logic-based signal timing optimization method and a speed control method are proposed for the connected and automated vehicles (CAV). The signal timing at the intersection can adapt to traffic demand dynamically, and the CAVs can optimize their speed strategy based on the prediction of the traffic states to pass the intersection efficiently and smoothly. Based on the reasonable speed control of the leading vehicle in the approach lanes during the green signal, the leading effect of the CAV can be utilized to avoid start-up loss and make the platoon pass the intersection efficiently. The simulation results show that the proposed cooperated control method can significantly reduce the average vehicle delay at intersections compared with the traditional control methods, and the logic-based decision making model can be solved efficiently. Based on the sensitivity analysis of the key parameters of the control strategy for the CAV, the fairness of the mixed traffic flow at intersection is further discussed, and the effectiveness of the control methods are compared for the mixed traffic with different penetration rates of CAVs. © 2023 Science Press. All rights reserved.