Collision Avoidance for Vehicle-Following Systems

TLDR: A planning and decision component to generalize vehicle following to situations with nonautomated interfering vehicles in mixed traffic by treating the path of the leader vehicle as an elastic band that is subjected to repelling forces of obstacles in the surroundings.

Abstract: The vehicle-following concept has been widely used in several intelligent-vehicle applications. Adaptive cruise control systems, platooning systems, and systems for stop-and-go traffic employ this concept: The ego vehicle follows a leader vehicle at a certain distance. The vehicle-following concept comes to its limitations when obstacles interfere with the path between the ego vehicle and the leader vehicle. We call such situations dynamic driving situations. This paper introduces a planning and decision component to generalize vehicle following to situations with nonautomated interfering vehicles in mixed traffic. As a demonstrator, we employ a car that is able to navigate autonomously through regular traffic that is longitudinally and laterally guided by actuators controlled by a computer. This paper focuses on and limits itself to lateral control for collision avoidance. Previously, this autonomous-driving capability was purely based on the vehicle-following concept using vision. The path of the leader vehicle was tracked. To extend this capability to dynamic driving situations, a dynamic path-planning component is introduced. Several driving situations are identified that necessitate responses to more than the leader vehicle. We borrow an idea from robotics to solve the problem. Treat the path of the leader vehicle as an elastic band that is subjected to repelling forces of obstacles in the surroundings. This elastic-band framework offers the necessary features to cover dynamic driving situations. Simulation results show the power of this approach. Real-world results obtained with our demonstrator validate the simulation results