Obstacle Avoidance for Low-Speed Autonomous Vehicles With Barrier Function

Yuxiao Chen, Huei Peng, Jessy W. Grizzle

Abstract: This paper presents an obstacle avoidance algorithm for low speed autonomous vehicles (AV), with guaranteed safety. A supervisory control algorithm is constructed based on a barrier function method, which works in a plug-and-play fashion with any lower level navigation algorithm. When the risk of collision is low, the barrier function is not active; when the risk is high, based on the distance to an “avoidable set,” the barrier function controller will intervene, using a mixed integer program to ensure safety with minimal control effort. This method is applied to solve the navigation and pedestrian avoidance problem of a low speed AV. Its performance is compared with two benchmark algorithms: a potential field method and the Hamilton-Jacobi method.