Collision-free motion control with learning features for automated vehicles in roundabouts

Abstract

Control design for safe and time-efficient motion of automated vehicles in roundabout scenarios poses various challenges, especially adaptation to the actual traffic scenario and coordination of the vehicles. This paper proposes the design of a hierarchical motion control with learning feature for roundabout scenarios. The control is designed on two levels, such as on cloud level and on vehicle level. The control on the cloud level is designed by using reinforcement learning (RL), with which the energy efficient motion of the vehicle is achieved. The vehicle level contains a robust controller and a supervisor, with which the collision avoidance of the vehicles is guaranteed. The proposed control on a Hardware-in-the-Loop environment with small-scaled indoor vehicles in augmented reality is implemented. The effectiveness of the control and the safe motion of the automated vehicles under multi-vehicle scenario are demonstrated. The provided scenario illustrates that safe, i.e., collision-free motion of all automated vehicles can be guaranteed.