Asleep at the automated wheel—Sleepiness and fatigue during highly automated driving. (May 2019)
- Record Type:
- Journal Article
- Title:
- Asleep at the automated wheel—Sleepiness and fatigue during highly automated driving. (May 2019)
- Main Title:
- Asleep at the automated wheel—Sleepiness and fatigue during highly automated driving
- Authors:
- Vogelpohl, Tobias
Kühn, Matthias
Hummel, Thomas
Vollrath, Mark - Abstract:
- Abstract: Due to the lack of active involvement in the driving situation and due to monotonous driving environments drivers with automation may be prone to become fatigued faster than manual drivers (e.g.Schömig et al., 2015 ). However, little is known about the progression of fatigue during automated driving and its effects on the ability to take back manual control after a take-over request. In this driving simulator study with N ö=ö60 drivers we used a three factorial 2ö×ö2ö×ö12 mixed design to analyze the progression (12ö×ö5ömin; within subjects) of driver fatigue in drivers with automation compared to manual drivers (between subjects). Driver fatigue was induced as either mainly sleep related or mainly task related fatigue (between subjects). Additionally, we investigated the drivers' reactions to a take-over request in a critical driving scenario to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving. Drivers in the automated driving condition exhibited facial indicators of fatigue after 15 to 35ömin of driving. Manual drivers only showed similar indicators of fatigue if they suffered from a lack of sleep and then only after a longer period of driving (approx. 40ömin). Several drivers in the automated condition closed their eyes for extended periods of time. In the driving with automation condition mean automation deactivation times after a take-over request were slower for a certain percentageAbstract: Due to the lack of active involvement in the driving situation and due to monotonous driving environments drivers with automation may be prone to become fatigued faster than manual drivers (e.g.Schömig et al., 2015 ). However, little is known about the progression of fatigue during automated driving and its effects on the ability to take back manual control after a take-over request. In this driving simulator study with N ö=ö60 drivers we used a three factorial 2ö×ö2ö×ö12 mixed design to analyze the progression (12ö×ö5ömin; within subjects) of driver fatigue in drivers with automation compared to manual drivers (between subjects). Driver fatigue was induced as either mainly sleep related or mainly task related fatigue (between subjects). Additionally, we investigated the drivers' reactions to a take-over request in a critical driving scenario to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving. Drivers in the automated driving condition exhibited facial indicators of fatigue after 15 to 35ömin of driving. Manual drivers only showed similar indicators of fatigue if they suffered from a lack of sleep and then only after a longer period of driving (approx. 40ömin). Several drivers in the automated condition closed their eyes for extended periods of time. In the driving with automation condition mean automation deactivation times after a take-over request were slower for a certain percentage (about 30%) of the drivers with a lack of sleep ( M ö=ö3.2; SD ö=ö2.1ös) compared to the reaction times after a long drive ( M ö=ö2.4; SD ö=ö0.9ös). Drivers with automation also took longer than manual drivers to first glance at the speed display after a take-over request and were more likely to stay behind a braking lead vehicle instead of overtaking it. Drivers are unable to stay alert during extended periods of automated driving without non-driving related tasks. Fatigued drivers could pose a serious hazard in complex take-over situations where situation awareness is required to prepare for threats. Driver fatigue monitoring or controllable distraction through non-driving tasks could be necessary to ensure alertness and availability during highly automated driving. … (more)
- Is Part Of:
- Accident analysis and prevention. Volume 126(2019)
- Journal:
- Accident analysis and prevention
- Issue:
- Volume 126(2019)
- Issue Display:
- Volume 126, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 126
- Issue:
- 2019
- Issue Sort Value:
- 2019-0126-2019-0000
- Page Start:
- 70
- Page End:
- 84
- Publication Date:
- 2019-05
- Subjects:
- Fatigue -- Sleep -- Automated driving -- Transition to manual -- Take-over request
Accidents -- Prevention -- Periodicals
Accident Prevention -- Periodicals
Accidents -- Prévention -- Périodiques
363.106 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00014575 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aap.2018.03.013 ↗
- Languages:
- English
- ISSNs:
- 0001-4575
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0573.130000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9987.xml