The on-ramp merge area is a typical bottleneck, which usually leads to traffic congestion and reduced traffic efficiency. As an emerging vehicle model, connected and autonomous vehicles (CAVs) can alleviate many traditional traffic problems. At present, the research on the cooperative merging control of CAVs in the on-ramp area is one of the research hotspots in the transportation field. In this paper, for cooperative on-ramp merging effects on upstream traffic in the on-ramp area, we designed a novel fully cooperative merging strategy based on the coordination of upstream and downstream vehicles firstly. Then, under the framework of model predictive control (MPC-framework), a heuristic optimization algorithm based on penalty function is adopted to design the cooperative merging controllers of cooperative vehicles and on-ramp vehicles. Through simulation experiments, we verified the effectiveness and advancement of the fully cooperative merging strategy proposed in this paper.

CICTP