NDLI: Detecting sleep in drivers during highly automated driving: the potential of physiological parameters

Content Provider	IET Digital Library
Author	Wörle, Johanna Metz, Barbara Thiele, Christian Weller, Gert
Abstract	Driver monitoring is added as a primary safety measure in the EuroNCAP roadmap 2025. Especially with the introduction of automated driving systems into the market, new requirements are set to driver monitoring systems (DMSs). When not being actively involved in driving, the risk of drivers becoming drowsy and even falling asleep at the wheel increases. Modern DMSs will have to be able to detect a driver falling asleep or sleeping in order for the automation to take appropriate actions. Conventional measures for detecting the driver state such as analysing the driving behaviour are not available in automated driving. The aim of the study was to identify potential physiological measures as a basis for the development of systems that are able to detect sleep in drivers during automated driving. A within-subjects study with N = 21 subjects was conducted in a high-fidelity driving simulator. Electromyography, electrodermal activity (EDA), respiration and electrocardiography (ECG) were measured in drivers during states of wakefulness and sleep. Sleep stages were assigned with the electroencephalography as a ground truth. The results indicate the potential of EDA and ECG parameters to differentiate between sleep and wakefulness. Implications for the implementation in DMS are discussed.
Starting Page	1241
Ending Page	1248
Page Count	8
ISSN	1751956X
Volume Number	13
e-ISSN	17519578
Issue Number	Issue 8, Aug (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5529
Journal	IET Intelligent Transport Systems
Publisher Date	2019-04-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Driving System Automation Bioelectric Signal Biology And Medical Computing Conventional Measures Digital Signal Processing DMS Driver Information System Driver Monitoring System Driver State Driving Behaviour ECG EDA Electrical Activity in Neurophysiological Processes Electrocardiography Electrodermal Activity Electrodiagnostics And Other Electrical Measurement Technique Electroencephalography Electromyography EuroNCAP Roadmap 2025 High-fidelity Driving Simulator Highly Automated Driving Medical Signal Processing Physiology Potential Physiological Measures Primary Safety Measure Respiration Road Accidents Road Safety Sleep Sleep Detection Traffic Engineering Computing Wakefulness
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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