ExplAIn Yourself! Transparency for Positive UX in Autonomous Driving
Tobias Schneider, Joana Hois, Alischa Rosenstein, Sabiha Ghellal, Dimitra Theofanou-Fülbier, Ansgar R. S. Gerlicher
Abstract
In a fully autonomous driving situation, passengers hand over the steering control to a highly automated system. Autonomous driving behaviour may lead to confusion and negative user experience. When establishing such new technology, the user’s acceptance and understanding are crucial factors regarding success and failure. Using a driving simulator and a mobile application, we evaluated if system transparency during and after the interaction can increase the user experience and subjective feeling of safety and control. We contribute an initial guideline for autonomous driving experience design, bringing together the areas of user experience, explainable artificial intelligence and autonomous driving. The AVAM questionnaire, UEQ-S and interviews show that explanations during or after the ride help turn a negative user experience into a neutral one, which might be due to the increased feeling of control. However, we did not detect an effect for combining explanations during and after the ride.
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