ATHENA

2019

Research on conditionally automated (SAE L3) vehicles usually addresses safety issues in the context of Take-OverRequests. However, little knowledge is available on how the mere possibility of upcoming control transfers affects drivers’ user experience.

To learn more about this problem we applied a design-thinking approach:

We conducted a focus group discussion applying the UX cards method. Results suggest that the psychological needs of security, autonomy, competence, and stimulation are not properly satisfied in SAE L3 driving.
To counteract, we developed a natural language reliability display (called “ATHENA”), aiming at satisfying these needs in different driving situations. ATHENA communicates the current level of required driver engagement and tries to make them more relaxed in phases of high automation performance while providing encouraging feedback after experiencing a TOR.

First results from a driving simulator study for evaluation (N=18) indicate that ATHENA, although not making drivers feel more autonomous, positively influenced their subjective feeling of safety while reducing negative affect.

We conclude, keeping the driver in the loop with a reliability display helps to improve driving experience by at least reducing negative affect, however, contradicts the promise of SAE L3. Hence, the introduction of SAE L3 is not only questionable from a safety (cf. statements from VOLVO), but also from an experiential perspective.

My part in the project

I came up with the original idea of this academic project as part of my dissertation.

I was responsible for the study design and the methodological setup which was inspired by the DAUX Framework.

I supervised prototyping and study conduction.

I analyzed the qualitative and quantitative data.

I was the leading author of the related publications.

Publications

AutoUI 2019

ATHENA: supporting UX of conditionally automated driving with natural language reliability displays