A Merging Strategy Based on Optimal Control of Main-lane Downstream and On-ramp Vehicles

The on-ramp merging on expressway is one of the hotspots of research, which usually leads to reduced traffic efficiency, increased risk of collision, and increased fuel consumption. However, most current on-ramp merging strategies coordinate merging by controlling upstream vehicles, which adversely effects on the main-lane traffic after the merging position (MP). To address this problem, this paper proposes an on-ramp merging strategy for connected and autonomous vehicles (CAVs) based on the collaboration of downstream main-lane vehicles and on-ramp vehicles. First, we propose a necessary communication topology to meet the information needs of vehicle collaboration in this strategy. Then, the downstream vehicles of the MP act using the feedback from the upstream vehicles of the MP to cooperate with the on-ramp vehicles. Meanwhile, in order to ensure the safe, we transform the vehicle control problem in the strategy into an optimization problem with state and input constraints, and the optimal solution is calculated using model predictive control (MPC). Finally, we use simulation experiments to verify, compare and analyze the proposed strategy. Simulation results show that the strategy is effective in preventing the deterioration of traffic conditions caused by merging behavior and has advantages in improving merging efficiency, reducing fuel consumption, and improving comfort.