Integrated control of traffic signal and automated vehicles for mixed traffic: Platoon-based bi-level optimization approach

Connected and autonomous vehicle (CAV) technologies are widely recognized to help improve the operational efficiency of urban road traffic systems and thus mitigate traffic congestion. In this study, we propose a bi-level integrated control method to optimize traffic signals and automated vehicle trajectories simultaneously for mixed traffic with human-driven vehicles (HDVs) and CAVs. Instead of considering individual vehicles in the optimization process, the vehicles are divided into platoons, which are used as the basic units for optimal control, such that the computational cost can be reduced. A mixed integer linear programming (MILP) model is developed to optimize the signal timing scheme and arrival time of the platoon at the stop line with the objective of minimizing the total delay. Based on the optimized arrival time, the trajectory of the first CAV in the moving platoon is optimized to reduce the start-stop phenomenon at the intersection. Numerical experiments are performed and the results demonstrate that the proposed method outperforms the vehicle-actuated control method significantly in terms of the delay and fuel consumption reduction under different traffic conditions. Furthermore, the performance improvement of the proposed model compared to that of the vehicle-actuated control method increases substantially with the increase of the CAV penetration rate.