Abstract
While using highly automated systems, various non-critical automated driving scenarios can be identified in which trust plays a role. In this study, we investigated the change of trust in these scenarios with a digital "Feeling of Trust"indicator, through video-based online experiments simulating automated driving. Initial results show that trust even changes in these scenarios and revealed multiple influential factors. While trust seems to drop consistently in certain cases, we found individual differences in other events. With our experimental setup and findings, we provide a tool to examine trust aspects in an online study. This contributes to the understanding of how to design human-vehicle interactions in highly automated cars with the goal to calibrate trust under ordinary non-critical events.
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CITATION STYLE
Dong, H., Martens, M., & Pfleging, B. (2021). An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios. In Adjunct Proceedings - 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 (pp. 34–38). Association for Computing Machinery, Inc. https://doi.org/10.1145/3473682.3480259
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