V2V-based Synchronous Intersection Protocols for Mixed Traffic of Human-Driven and Self-Driving Vehicles

Self-driving vehicles are expected to be at the core of future transportation systems. Over time, these vehicles might enhance traffic efficiency and safety, especially at road intersections. However, there will likely be a long transition period before human-driven vehicles will be completely replaced by automated vehicles. Intersection safety and efficiency might be barely improved if automated vehicles just follow the traffic light signals. In this paper, we present a decentralized intersection protocol named the Distributed Synchronous Intersection Protocol (DSIP) that is for mixed traffic environments, where human-driven and self-driving vehicles cooperate with one another in order to avoid vehicle collisions and possible deadlocks while improving traffic efficiency. In DSIP, all automated vehicles use both Vehicle-to-Vehicle (V2V) communications and traffic lights to traverse the intersection safely. On the other hand, human-driven vehicles simply follow the traffic lights just like they do today. Under the protocol, the automated vehicles synchronize when there are no human-driven vehicles around the intersection. In addition, Cooperative Perception is used to detect the presence of human-driven vehicles, where all automated and connected vehicles sense and share the presence of the human-driven vehicles at the intersection. Our simulation results show that DSIP increases the traffic throughput of the intersections compared to common signalized intersections and other V2V-based intersection protocols.