Sleep inertia in automated driving: Post-sleep take-over and driving performance.

Automated driving Driver state Driving performance Sleep Sleep inertia Take-over performance

Journal

Accident; analysis and prevention
ISSN: 1879-2057
Titre abrégé: Accid Anal Prev
Pays: England
ID NLM: 1254476

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 31 07 2020
revised: 23 11 2020
accepted: 24 11 2020
pubmed: 15 12 2020
medline: 16 6 2021
entrez: 14 12 2020
Statut: ppublish

Résumé

Sleep is emerging as a new driver state in automated driving. Post-sleep performance impairments due to sleep inertia, the transitional phase from sleep to wakefulness that can take up to 30 min, are a potential safety issue. Take-over performance immediately after sleep is impaired and drivers perceive the take-over as critical. The aim of the presented study was to assess take-over behavior immediately after sleep and driving behavior during the 10 min after sleep. A study with N = 31 drivers was conducted in a high-fidelity driving simulator. Take-over performance and driving performance were assessed a) under alert baseline conditions and b) after awakening from electroencephalography-confirmed stable sleep. Take-over performance 15 s after awakening was impaired resulting in more driving errors compared to the alert baseline. Lane keeping was dramatically impaired in the first 3 min after sleep and recovered rapidly. Drivers drove slower after sleep and speed keeping was less stable for at least 10 min. The results suggest that human-machine interaction design should account for the drivers' impaired post-sleep driving performance.

Identifiants

pubmed: 33310649
pii: S0001-4575(20)31738-3
doi: 10.1016/j.aap.2020.105918
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105918

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Johanna Wörle (J)

Würzburg Institute for Traffic Sciences, Germany; University of Ulm, Germany. Electronic address: woerle@wivw.de.

Barbara Metz (B)

Würzburg Institute for Traffic Sciences, Germany. Electronic address: metz@wivw.de.

Martin Baumann (M)

University of Ulm, Germany. Electronic address: martin.baumann@uni-ulm.de.

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