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Ramp merging is considered as one of the major causes of traffic congestionand accidents because of its chaotic nature. With the development of connectedand automated vehicle (CAV) technology, cooperative ramp merging has become oneof the popular solutions to this problem. In a mixed traffic situation, CAVswill not only interact with each other, but also handle complicated situationswith human-driven vehicles involved. In this paper, a game theory-based rampmerging strategy has been developed for the optimal merging coordination ofCAVs in the mixed traffic, which determines dynamic merging sequence andcorresponding longitudinal/lateral control. This strategy improves the safetyand efficiency of the merging process by ensuring a safe inter-vehicle distanceamong the involved vehicles and harmonizing the speed of CAVs in the trafficstream. To verify the proposed strategy, mixed traffic simulations underdifferent penetration rates and different congestion levels have been carriedout on an innovative Unity-SUMO integrated platform, which connects a gameengine-based driving simulator with a traffic simulator. This platform allowsthe human driver to participate in the simulation, and also equip CAVs withmore realistic sensing systems. In the traffic flow level simulation test,Unity takes over the sensing and control of all CAVs in the simulation, whileSUMO handles the behavior of all legacy vehicles. The results show that theaverage speed of traffic flow can be increased up to 110%, and the fuelconsumption can be reduced up to 77%, respectively.

A Game Theory Based Ramp Merging Strategy for Connected and Automated Vehicles in the Mixed Traffic: A Unity-SUMO Integrated Platform