Reservation-Based Cooperative Ecodriving Model for Mixed Autonomous and Manual Vehicles at Intersections

Oversaturation has become a serious issue for urban intersections worldwide due to the rapid increase in population and traffic demands. The emergence of connected and automated vehicle (CAV) technologies demonstrates the potential to improve oversaturated arterial traffic. Integrating vehicular control and intersection controller optimization into a single process based on CAV technologies can optimize the performance of mixed traffic flow scenarios with various levels of CAV market penetration. This paper proposes an efficient reservation-based cooperative ecodriving model (RCEM) for an isolated intersection under partial and complete CAV market penetration, which can simultaneously optimize the CAV trajectories and intersection controller. CAVs are utilized to precluster manual vehicles into a platoon to improve vehicle passage efficiency. Then, a heuristic-based algorithm is developed to effectively obtain an optimal solution. The proposed RCEM scheme is compared with fixed signal control and actuated signal control in a Simulation of Urban MObility (SUMO)-based platform. Experimental results prove that the RCEM scheme outperforms the fixed signal control and actuated signal control in terms of stop delay, fuel consumption, and emissions under the condition of low levels of CAV penetration. Sensitivity analysis indicates that the system performance further improves as the CAV penetration rate increases, and the stop delay is almost eliminated when the CAV market penetration reaches 100%. Furthermore, the vehicle delay fluctuation under left-turning rates ranging from 5%-75% is 4.4 sec, which is far better than the vehicle delay fluctuation of the fixed signal control (176 sec) and actuated control (65.6 sec).