Toward Integrated Takeover Performance Measurement: Validation of Fréchet Distance as a Takeover Performance Metric
This study introduces and validates a new metric for assessing takeover performance in conditionally automated driving, using Fréchet Distance. Fréchet Distance is a measurement that measures the similarity between two separate curves. Thirty-two participants took part in a simulated driving experiment. Employing a 2 × 2 within-subjects design, the study compared traditional takeover performance metrics, including takeover time, time to collision, and resulting acceleration, with Fréchet Distance. Analysis results revealed similar trends between traditional metrics and Fréchet Distance. These findings suggest that Fréchet Distance can effectively measure takeover performance by integrating spatial and temporal aspects.
Authors
- Dawn M. Tilbury (ORCID: https://orcid.org/0000-0002-2510-0556)
- Jundi Liu (ORCID: https://orcid.org/0000-0001-6979-3166)
- Lisa J. Molnar (ORCID: https://orcid.org/0000-0002-9556-1761)
- Doo Won Han (ORCID: https://orcid.org/0000-0003-2715-2912)
- William J. Horrey (ORCID: https://orcid.org/0000-0002-9533-4411)
- X. Jessie Yang (ORCID: https://orcid.org/0009-0000-8251-9268)
- Lionel Robert (ORCID: https://orcid.org/0000-0002-1410-2601)
- Alicia Romo
- Zhou Feng (ORCID: https://orcid.org/0000-0001-8186-3104)
Institutions
- AAA Foundation for Traffic Safety (US)
- Michigan Department of Transportation (US)
- University of Michigan (US)
- University of Michigan–Dearborn (US)
Publication Details
- Journal
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1177/10711813241266831
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00