Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving

Christopher Cabrall; Nico Janssen; Joel Goncalves; Alberto Morando; Matthew Sassman; Joost De Winter

doi:10.1109/SMC.2016.7844530

Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving

Christopher Cabrall, Nico Janssen, Joel Goncalves, Alberto Morando, Matthew Sassman, Joost De Winter

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

9 Citations (Scopus)

44 Downloads (Pure)

Abstract

Automated driving vehicles of the future will most likely include multiple modes and levels of operation and thus include various transitions of control (ToC) between human and machine. Traditional activation devices (e.g., knobs, switches, buttons, and touchscreens) may be confused by operators among other system setting manipulators and also susceptible to inappropriate usage. Non-intrusive eye-tracking measures may assess driver states (i.e., distraction, drowsiness, and cognitive overload) automatically to trigger manual-to-automation ToC and serve as a driver readiness verification during automation-to-manual ToC. Our integrated driver state monitor is overviewed here within the scope of this brief system description/demonstration paper. It combines gaze position, gaze variability, eyelid opening, as well as external environmental complexity from the driving scene to facilitate ToC in automated driving. As both driver facing and forward facing cameras become increasingly commonplace and even legally mandated within various automated driving vehicles, our integrated system helps inform relevant future research and development towards improved human-computer interaction and driving safety.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics
Subtitle of host publication	SMC 2016
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	1981-1982
ISBN (Electronic)	978-1-5090-1897-0
DOIs	https://doi.org/10.1109/SMC.2016.7844530
Publication status	Published - 2016
Event	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary Duration: 9 Oct 2016 → 12 Oct 2016

Conference

Conference	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/Territory	Hungary
City	Budapest
Period	9/10/16 → 12/10/16

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Vehicles
Automation
Monitoring
Safety
Roads
Bars
Time measurement

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10.1109/SMC.2016.7844530

07844530Final published version, 2.01 MB

Cite this

Cabrall, C., Janssen, N., Goncalves, J., Morando, A., Sassman, M., & De Winter, J. (2016). Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving. In Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics: SMC 2016 (pp. 1981-1982). IEEE . https://doi.org/10.1109/SMC.2016.7844530

Cabrall, Christopher ; Janssen, Nico ; Goncalves, Joel ; Morando, Alberto ; Sassman, Matthew ; De Winter, Joost. / Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics: SMC 2016 . Piscataway, NJ, USA : IEEE , 2016. pp. 1981-1982

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abstract = "Automated driving vehicles of the future will most likely include multiple modes and levels of operation and thus include various transitions of control (ToC) between human and machine. Traditional activation devices (e.g., knobs, switches, buttons, and touchscreens) may be confused by operators among other system setting manipulators and also susceptible to inappropriate usage. Non-intrusive eye-tracking measures may assess driver states (i.e., distraction, drowsiness, and cognitive overload) automatically to trigger manual-to-automation ToC and serve as a driver readiness verification during automation-to-manual ToC. Our integrated driver state monitor is overviewed here within the scope of this brief system description/demonstration paper. It combines gaze position, gaze variability, eyelid opening, as well as external environmental complexity from the driving scene to facilitate ToC in automated driving. As both driver facing and forward facing cameras become increasingly commonplace and even legally mandated within various automated driving vehicles, our integrated system helps inform relevant future research and development towards improved human-computer interaction and driving safety.",

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author = "Christopher Cabrall and Nico Janssen and Joel Goncalves and Alberto Morando and Matthew Sassman and {De Winter}, Joost",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

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Cabrall, C, Janssen, N, Goncalves, J, Morando, A, Sassman, M & De Winter, J 2016, Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving. in Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics: SMC 2016 . IEEE , Piscataway, NJ, USA, pp. 1981-1982, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 9/10/16. https://doi.org/10.1109/SMC.2016.7844530

Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving. / Cabrall, Christopher; Janssen, Nico; Goncalves, Joel; Morando, Alberto; Sassman, Matthew; De Winter, Joost.

Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics: SMC 2016 . Piscataway, NJ, USA : IEEE , 2016. p. 1981-1982.

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

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AU - Sassman, Matthew

AU - De Winter, Joost

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N2 - Automated driving vehicles of the future will most likely include multiple modes and levels of operation and thus include various transitions of control (ToC) between human and machine. Traditional activation devices (e.g., knobs, switches, buttons, and touchscreens) may be confused by operators among other system setting manipulators and also susceptible to inappropriate usage. Non-intrusive eye-tracking measures may assess driver states (i.e., distraction, drowsiness, and cognitive overload) automatically to trigger manual-to-automation ToC and serve as a driver readiness verification during automation-to-manual ToC. Our integrated driver state monitor is overviewed here within the scope of this brief system description/demonstration paper. It combines gaze position, gaze variability, eyelid opening, as well as external environmental complexity from the driving scene to facilitate ToC in automated driving. As both driver facing and forward facing cameras become increasingly commonplace and even legally mandated within various automated driving vehicles, our integrated system helps inform relevant future research and development towards improved human-computer interaction and driving safety.

AB - Automated driving vehicles of the future will most likely include multiple modes and levels of operation and thus include various transitions of control (ToC) between human and machine. Traditional activation devices (e.g., knobs, switches, buttons, and touchscreens) may be confused by operators among other system setting manipulators and also susceptible to inappropriate usage. Non-intrusive eye-tracking measures may assess driver states (i.e., distraction, drowsiness, and cognitive overload) automatically to trigger manual-to-automation ToC and serve as a driver readiness verification during automation-to-manual ToC. Our integrated driver state monitor is overviewed here within the scope of this brief system description/demonstration paper. It combines gaze position, gaze variability, eyelid opening, as well as external environmental complexity from the driving scene to facilitate ToC in automated driving. As both driver facing and forward facing cameras become increasingly commonplace and even legally mandated within various automated driving vehicles, our integrated system helps inform relevant future research and development towards improved human-computer interaction and driving safety.

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M3 - Conference contribution

SP - 1981

EP - 1982

BT - Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics

PB - IEEE

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ER -

Cabrall C, Janssen N, Goncalves J, Morando A, Sassman M, De Winter J. Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving. In Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics: SMC 2016 . Piscataway, NJ, USA: IEEE . 2016. p. 1981-1982 https://doi.org/10.1109/SMC.2016.7844530

Eye-based driver state monitor of distraction, drowsiness, and cognitive load for transitions of control in automated driving

Abstract

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Keywords

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