Drowsiness in conditional automation

Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects

Goncalves, J.
Happee, R. (TU Delft OLD Intelligent Vehicles & Cognitive Robotics)
Bengler, KJ

Rosetti, R. (editor)
Wolf, D. (editor)

2016

Fatigue and drowsiness can play an important role in Conditional Automation (CA), as drowsy drivers may fail to properly recover control. In order to provide better insight in the effects of drowsy driving in Take Over Request (TOR), we designed a driving experiment that extends related literature in drowsiness research CA with self-rated subjective drowsiness, and analyze TOR performance adopting methods from recent TOR publications. Results show that under certain conditions, drivers are very prone to drowsiness. Specifically, in this study the majority of subjects reported a high level of drowsiness before 15 minutes. Furthermore, this self-perceived drowsiness was followed by a decrement in vehicle lateral control during TOR. In this time frame, remaining driving performance and eye-Tracking related metrics did not show significant decrements traditionally associated with fatigue and drowsiness, suggesting self-report to be more indicative of drowsiness than eye-based metrics.

http://resolver.tudelft.nl/uuid:58e3a150-a9c4-4fa8-aaec-c051a05e0fb1

https://doi.org/10.1109/ITSC.2016.7795658

Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA

9781509018895

Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016

ITSC 2016: 19th International Conference on Intelligent Transportation Systems, 2016-11-01 → 2016-12-04, Rio de Janeiro, Brazil

Institutional Repository

conference paper

© 2016 J. Goncalves, R. Happee, KJ Bengler