Decentralized Cooperative Collision Avoidance for Automated Vehicles: a Real-World Implementation

Connected and automated vehicles provide a new opportunity for collision avoidance, in which several cars cooperate to reach an optimal overall outcome. However, this requires solving the challenging real-time problem of global designing of the joint trajectories that a group of cooperating vehicles should follow to avoid the obstacle and mutually avoid each other. The leaderless method demonstrated here uses the notion of “desired” versus “planned” trajectories, allowing vehicles to influence each other for mutual benefit: each vehicle attempts to avoid independently the desired trajectories of other vehicles, and thus cooperative behavior emerges. Each vehicle is equipped with a model predictive controller that optimizes both its trajectories. This flexible, decentralized method has been executed in a novel demonstration, using two full-sized vehicles on a test track, and results of the fully automated cooperative behavior achieved are presented.