  Ramp merging is considered as one of the major causes of traffic congestion
and accidents because of its chaotic nature. With the development of connected
and automated vehicle (CAV) technology, cooperative ramp merging has become one
of the popular solutions to this problem. In a mixed traffic situation, CAVs
will not only interact with each other, but also handle complicated situations
with human-driven vehicles involved. In this paper, a game theory-based ramp
merging strategy has been developed for the optimal merging coordination of
CAVs in the mixed traffic, which determines dynamic merging sequence and
corresponding longitudinal/lateral control. This strategy improves the safety
and efficiency of the merging process by ensuring a safe inter-vehicle distance
among the involved vehicles and harmonizing the speed of CAVs in the traffic
stream. To verify the proposed strategy, mixed traffic simulations under
different penetration rates and different congestion levels have been carried
out on an innovative Unity-SUMO integrated platform, which connects a game
engine-based driving simulator with a traffic simulator. This platform allows
the human driver to participate in the simulation, and also equip CAVs with
more realistic sensing systems. In the traffic flow level simulation test,
Unity takes over the sensing and control of all CAVs in the simulation, while
SUMO handles the behavior of all legacy vehicles. The results show that the
average speed of traffic flow can be increased up to 110%, and the fuel
consumption can be reduced up to 77%, respectively.
