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Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation

We investigate if an on-screen agent that reacts to a teleoperator’s driving performance (e.g., by showing fear during poor driving) can influence teleoperation. Serving as a kind of virtual passenger, we explore if and how this agent’s reactions may impact teleoperation. Our design concept is to create an emotional response in the operator (e.g., to feel bad for the agent), with the ultimate goal of shaping driving behavior (e.g., to slow down to calm the agent). We designed and implemented two proof-ofconcept passenger-agent personas that react differently to operator driving. By conducting an initial proof-of-concept study comparing our agents to a base case, we were able to observe the impact of our agent personas on operator experience, perception of the robot, and driving behavior. While our results failed to find compelling evidence of changed teleoperator behavior, we did demonstrate that emotional on-screen agents can alter teleoperator emotion. Our initial results support the plausibility of passenger agents for impacting teleoperation, and highlight potential for more targeted, ongoing work in applying social techniques to teleoperation interfaces.

Daniel J. Rea, James E. Young, "Backseat Teleoperator: affective feedback with on-screen agents to influence teleoperation." The ACM/IEEE International Conference on Human-Robot Interaction (HRI'19). ACM/IEEE. 2019.

Authors

Daniel J. Rea

Daniel J. Rea

PhD Student
James E.Young

James E.Young

Associate Professor