Safe and efficient collision avoidance control for autonomous vehicles

We study a novel principle for safe and efficient collision avoidance that adopts a mathematically elegant and general framework making as much as possible abstraction of the controlled vehicle's dynamics and of its environment. Vehicle dynamics is characterized by pre-computed functions for accelerating and braking to a given speed. Environment is modeled by a function of time giving the free distance ahead of the controlled vehicle under the assumption that the obstacles are either fixed or are moving in the same direction. The main result is a control policy enforcing the vehicle's speed so as to avoid collision and efficiently use the free distance ahead, provided some initial safety condition holds. The studied principle is applied to the design of a synchronous controller. We show that the controller is safe by construction. Furthermore, we show that the efficiency strictly increases for decreasing granularity of discretization. We present the implementation and experimental evaluations in the Carla autonomous driving simulator and investigate various performance issues.