The Biasing of Action Selection Produces Emergent Human-Robot Interactions in Autonomous Driving

This letter describes a means to produce emergent collaboration between human driver and an artificial co-driver agent. The work exploits the hypothesis that human-human cooperation emerges from shared understanding of given context’s affordances emulates same principle: observation one agent’s behavior steers another decision-making by favoring selection goals would observed activity. Specifically, we describe how steer special self-driving agent via weighting action process with input dummy driving In this way, maps onto safe affordable actions recognized We demonstrate efficient driving, collaboration, rejection unsafe requests.