Eye-Gaze Analysis of HUD Interventions for Conditional Automation to Increase Situation Awareness
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.
Michael A. Gerber, Roland Schroeter, Daniel Johnson, and Andry Rakotonirainy. 2021. Eye-Gaze Analysis of HUD Interventions for Conditional Automation to Increase Situation Awareness. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI ’21 Adjunct), September 9–14, 2021, Leeds, United Kingdom. ACM, New York, NY, USA, https://doi.org/10.1145/3473682.3481872