This content will become publicly available on May 13, 2025
- Award ID(s):
- 1846210
- NSF-PAR ID:
- 10520725
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400701726
- Page Range / eLocation ID:
- 887 to 890
- Format(s):
- Medium: X
- Location:
- Singapore Singapore
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Objective This study explores subjective and objective driving style similarity to identify how similarity can be used to develop driver-compatible vehicle automation.
Background Similarity in the ways that interaction partners perform tasks can be measured subjectively, through questionnaires, or objectively by characterizing each agent’s actions. Although subjective measures have advantages in prediction, objective measures are more useful when operationalizing interventions based on these measures. Showing how objective and subjective similarity are related is therefore prudent for aligning future machine performance with human preferences.
Methods A driving simulator study was conducted with stop-and-go scenarios. Participants experienced conservative, moderate, and aggressive automated driving styles and rated the similarity between their own driving style and that of the automation. Objective similarity between the manual and automated driving speed profiles was calculated using three distance measures: dynamic time warping, Euclidean distance, and time alignment measure. Linear mixed effects models were used to examine how different components of the stopping profile and the three objective similarity measures predicted subjective similarity.
Results Objective similarity using Euclidean distance best predicted subjective similarity. However, this was only observed for participants’ approach to the intersection and not their departure.
Conclusion Developing driving styles that drivers perceive to be similar to their own is an important step toward driver-compatible automation. In determining what constitutes similarity, it is important to (a) use measures that reflect the driver’s perception of similarity, and (b) understand what elements of the driving style govern subjective similarity.
