Schwindt-Drews, Sarah ; Abendroth, Bettina (2025)
From Concept to Action - Measuring General and Applied Mental Models in the Context of Automated Driving.
The 9th international conference on driver distraction and inattention. Ann Arbor, USA (22.10.2024-24.10.2024)
doi: 10.26083/tuprints-00028976
Conference or Workshop Item, Secondary publication, Publisher's Version
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| Item Type: | Conference or Workshop Item |
|---|---|
| Type of entry: | Secondary publication |
| Title: | From Concept to Action - Measuring General and Applied Mental Models in the Context of Automated Driving |
| Language: | English |
| Date: | 7 January 2025 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | October 2024 |
| Collation: | 4 Seiten |
| Event Title: | The 9th international conference on driver distraction and inattention |
| Event Location: | Ann Arbor, USA |
| Event Dates: | 22.10.2024-24.10.2024 |
| DOI: | 10.26083/tuprints-00028976 |
| Corresponding Links: | |
| Abstract: | This paper presents a research concept for comparing general and applied mental models in automated driving, with a focus on the transition between automation levels. The research concept measures general and applied mental models, gaze movement, and driving performance within a driving simulator. It aims to correlate different mental models with driving performance, to identify how mental models should be characterized for safe interaction, and to provide insights for developing effective training concepts to improve user interaction with automated systems. |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-289768 |
| Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
| Divisions: | 16 Department of Mechanical Engineering > Ergonomics (IAD) 16 Department of Mechanical Engineering > Ergonomics (IAD) > Vehicle Ergonomics |
| Date Deposited: | 07 Jan 2025 13:11 |
| Last Modified: | 08 Jan 2025 08:01 |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/28976 |
| PPN: | 525088741 |
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