Eye-Gaze Analysis of HUD Interventions for Conditional Automation to Increase Situation Awareness

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Abstract

Automated driving seems promising to reduce crashes caused by human error. However, in the transition towards automated driving, a human is still required in some automation levels in some circumstances. Specifically, in conditional automation or SAE Level 3, a human needs to be able to continue the driving task any time the vehicle requests it. This means that throughout the L3 automated driving, this "fallback-ready user"needs to remain in a state to continue driving, even when they are engaged in other tasks, such as watching a movie. We designed three interventions with the aim to increase their fallback-readiness and have tested them in a high-fidelity video driving simulation study. In this video, we present and describe the interventions, the study design and the setup to test the interventions.

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Gerber, M. A., Schroeter, R., Johnson, D., & Rakotonirainy, A. (2021). Eye-Gaze Analysis of HUD Interventions for Conditional Automation to Increase Situation Awareness. In Adjunct Proceedings - 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 (pp. 210–212). Association for Computing Machinery, Inc. https://doi.org/10.1145/3473682.3481872

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