Cooperative Autonomous Driving for Urban Intersections Assisted by Vehicular Sensor Networks

Abstract

The current autonomous driving vehicles cannot collaborate with each other due to the disconnection of sensors between vehicles, which leads to poor performance in traffic efficiency and safety. Recently, with the development of wireless intelligent sensors, vehicular sensor network (VSN) is emerging to provide information sharing between vehicles, so that cooperative autonomous driving (CAD) can be enabled. This paper especially investigates the VSN-assisted straight-going CAD at urban intersections under the rule of traffic signals. First, the function of VSN is presented, and the information sharing mechanism is designed. Then distributed stop-and-go strategies with maintaining the optimal safety spacing between adjacent vehicles are proposed for multiple traffic cases. With the proposed strategies, every vehicle can get an exact time to decelerate or accelerate at signalized intersections. Finally, we use the model predictive control (MPC) scheme to actuate our strategies, and it is demonstrated that vehicles perform well in both passage safety and efficiency as expected.