Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects

J. Goncalves; Riender Happee; KJ Bengler

doi:10.1109/ITSC.2016.7795658

Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects

J. Goncalves, Riender Happee, KJ Bengler

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

33 Citations (Scopus)

382 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016
Editors	R. Rosetti, D. Wolf
Place of Publication	Piscataway, NJ, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	873-878
ISBN (Electronic)	9781509018895
DOIs	https://doi.org/10.1109/ITSC.2016.7795658
Publication status	Published - 2016
Event	ITSC 2016: 19th International Conference on Intelligent Transportation Systems - Rio de Janeiro, Brazil Duration: 1 Nov 2016 → 4 Dec 2016 Conference number: 19

Conference

Conference	ITSC 2016: 19th International Conference on Intelligent Transportation Systems
Abbreviated title	ITSC 2016
Country/Territory	Brazil
City	Rio de Janeiro
Period	1/11/16 → 4/12/16

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10.1109/ITSC.2016.7795658

Goncalves Happee Bengler Drowsiness in Conditional Automation ITSC2016Accepted author manuscript, 852 KB

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Goncalves, J., Happee, R., & Bengler, KJ. (2016). Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects. In R. Rosetti, & D. Wolf (Eds.), Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016 (pp. 873-878). Article 7795658 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ITSC.2016.7795658

Goncalves, J. ; Happee, Riender ; Bengler, KJ. / Drowsiness in conditional automation : Proneness, diagnosis and driving performance effects. Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. editor / R. Rosetti ; D. Wolf. Piscataway, NJ, USA : Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 873-878

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title = "Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects",

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.",

author = "J. Goncalves and Riender Happee and KJ Bengler",

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doi = "10.1109/ITSC.2016.7795658",

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note = "ITSC 2016: 19th International Conference on Intelligent Transportation Systems, ITSC 2016 ; Conference date: 01-11-2016 Through 04-12-2016",

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Goncalves, J, Happee, R & Bengler, KJ 2016, Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects. in R Rosetti & D Wolf (eds), Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016., 7795658, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, pp. 873-878, ITSC 2016: 19th International Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil, 1/11/16. https://doi.org/10.1109/ITSC.2016.7795658

Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects. / Goncalves, J.; Happee, Riender; Bengler, KJ.
Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. ed. / R. Rosetti; D. Wolf. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 873-878 7795658.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AB - 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.

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Goncalves J, Happee R, Bengler KJ. Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects. In Rosetti R, Wolf D, editors, Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 873-878. 7795658 doi: 10.1109/ITSC.2016.7795658

Drowsiness in conditional automation: Proneness, diagnosis and driving performance effects

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