Conference Proceeding

It’s Out of Our Hands Now! Effects of Non-Driving Related Tasks During Highly Automated Driving on Drivers’ Fatigue

Authors
  • Oliver Jarosch (BMW Group Research and Technology, Munich, Germany)
  • Matthias Kuhnt (Chemnitz University of Technology, Chemnitz, Germany)
  • Svenja Paradies (BMW Group Research and Technology, Munich, Germany)
  • Klaus Bengler (Technical University of Munich, Munich, Germany)

Abstract

With introduction of conditional automation in vehicles the driver can engage in non-driving related tasks (NDRTs) and only has to intervene in case of take-over requests (TOR). Therefore, active fatigue, which is the most frequent form of fatigue in manual driving, is assumed to be replaced by passive fatigue, intensified through monotony and monitoring tasks in conditional automated driving (CAD), SAE Level 3. To investigate effects of NDRTs on drivers’ fatigue and take over capability a driving simulator study was conducted. In total, 56 participants experienced two rides on a highway with CAD. During the two rides, participants had to fulfill both a monotonous monitoring task and an activating task. As in CAD the system is executing longitudinal and lateral control, drowsiness detection referring to driving performance becomes inoperative. Noninvasive methods for drowsiness detection that are not related to driving performance have to be investigated. Therefore, fatigue was measured with percentage of eye-lid closure (PERCLOS), blink related eye-tracking parameters, and the self-report Karolinska Sleepiness Scale (KSS). Results suggest that fatigue can be caused through a monitoring task in highly automated driving. PERCLOS could be confirmed as a valid parameter for detecting fatigue in CAD. Further, passive task related fatigue caused by a 25 min monotonous monitoring task does not affect the drivers’ take over capability negatively.

How to Cite:

Jarosch, O. & Kuhnt, M. & Paradies, S. & Bengler, K., (2017) “It’s Out of Our Hands Now! Effects of Non-Driving Related Tasks During Highly Automated Driving on Drivers’ Fatigue”, Driving Assessment Conference 9(2017), 319-325. doi: https://doi.org/10.17077/drivingassessment.1653

Rights: Copyright © 2017 the author(s)

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Published on
29 Jun 2017
Peer Reviewed