Drowsiness in conditional automation

Proneness, diagnosis and driving performance effects

Conference paper (2016)

Authors

R. Happee OLD Intelligent Vehicles & Cognitive Robotics
Research Group
OLD Intelligent Vehicles & Cognitive Robotics
Copyright: © 2016 J. Goncalves, R. Happee, KJ Bengler
DOI
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https://doi.org/10.1109/ITSC.2016.7795658
More Info
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Published Date

2016

Language

English

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Research Group

OLD Intelligent Vehicles & Cognitive Robotics

Abstract

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.