Asymmetry-based Behavior Planning for Cooperation at Shared Traffic Spaces

Many everyday traffic situations require cooperation among traffic participants to establish the order in which they pass a shared part of the road. Behavior planners which do not take this cooperative aspect into account properly struggle to find efficient solutions if the situation is nontrivial. Improper modelling may lead to overly aggressive or conservative behavior. In this paper, we propose an extension to state-of-the-art systems that enables behavior planners to efficiently cope with narrow passage scenarios even without car-to-car communication. The extended system is based on an asymmetry measure which takes the shared traffic space and the cooperation partners into account. This measure is then used to continuously predict which potential outcome is more likely to occur, to infer the assumed strategy of the cooperation partner, and to match the own strategy accordingly. Experiments show that the proposed system significantly reduces the cumulative passing time of the shared traffic space as compared to baseline systems. The resulting solutions are robust against variations in the behavior of both cooperation partners, and explicitly account for oblivious traffic participants which behave uncooperatively.