Handling Trust Between Drivers and Automated Vehicles for Improved Collaboration

Advances in perception and artificial intelligence technology are expected to lead to seamless interaction between humans and robots. Trust in robots has been evolving from the theory on trust in automation, with a fundamental difference: unlike traditional automation, robots could adjust their behaviors depending on how their human counterparts appear to be trusting them or how humans appear to be trustworthy. In this extended abstract I present my research on methods for processing trust in the particular context of interactions between a driver and an automated vehicle, which has the goal of achieving higher safety and performance standards for the team formed by those human and robotic agents.