Towards a real-time driver workload estimator: An on-the-road study

Peter Van Leeuwen; Renske Landman; Lejo Buning; Tobias Heffelaar; Jeroen Hogema; Jasper Michiel van Hemert; Joost de Winter; Riender Happee

doi:10.1007/978-3-319-41682-3_94

Towards a real-time driver workload estimator: An on-the-road study

Peter Van Leeuwen^*, Renske Landman, Lejo Buning, Tobias Heffelaar, Jeroen Hogema, Jasper Michiel van Hemert, Joost de Winter, Riender Happee

^*Corresponding author for this work

Biomechatronics & Human-Machine Control

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

5 Citations (Scopus)

54 Downloads (Pure)

Abstract

Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driver’s workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.

Original language	English
Title of host publication	Advances in Human Aspects of Transportation
Subtitle of host publication	Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation
Editors	Neville A. Stanton, Steven Landry, Giuseppe Di Bucchianico, Andrea Vallicelli
Place of Publication	Cham, Switzerland
Publisher	Springer
Pages	1151-1164
Volume	484
ISBN (Electronic)	978-3-319-41682-3
ISBN (Print)	978-3-319-41681-6
DOIs	https://doi.org/10.1007/978-3-319-41682-3_94
Publication status	Published - 2016
Event	7 th International Conference on Human Factors in Transportation - Orlando, United States Duration: 27 Jul 2016 → 31 Jul 2016

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	484
ISSN (Print)	21945357

Conference

Conference	7 th International Conference on Human Factors in Transportation
Abbreviated title	AHFE 2016
Country/Territory	United States
City	Orlando
Period	27/07/16 → 31/07/16

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

Adaptive in-vehicle information (systems)
Driver distraction
Driver workload estimation

Access to Document

10.1007/978-3-319-41682-3_94

Leeuwen2017_Chapter_TowardsAReal-TimeDriverWorkloa-1Final published version, 793 KB

Cite this

Van Leeuwen, P., Landman, R., Buning, L., Heffelaar, T., Hogema, J., van Hemert, J. M., de Winter, J., & Happee, R. (2016). Towards a real-time driver workload estimator: An on-the-road study. In N. A. Stanton, S. Landry, G. Di Bucchianico, & A. Vallicelli (Eds.), Advances in Human Aspects of Transportation : Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation (Vol. 484, pp. 1151-1164). (Advances in Intelligent Systems and Computing; Vol. 484). Springer. https://doi.org/10.1007/978-3-319-41682-3_94

Van Leeuwen, Peter ; Landman, Renske ; Buning, Lejo et al. / Towards a real-time driver workload estimator : An on-the-road study. Advances in Human Aspects of Transportation : Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation. editor / Neville A. Stanton ; Steven Landry ; Giuseppe Di Bucchianico ; Andrea Vallicelli. Vol. 484 Cham, Switzerland : Springer, 2016. pp. 1151-1164 (Advances in Intelligent Systems and Computing).

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title = "Towards a real-time driver workload estimator: An on-the-road study",

abstract = "Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driver{\textquoteright}s workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.",

keywords = "Adaptive in-vehicle information (systems), Driver distraction, Driver workload estimation",

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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.; 7 th International Conference on Human Factors in Transportation, AHFE 2016 ; Conference date: 27-07-2016 Through 31-07-2016",

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Van Leeuwen, P, Landman, R, Buning, L, Heffelaar, T, Hogema, J, van Hemert, JM, de Winter, J & Happee, R 2016, Towards a real-time driver workload estimator: An on-the-road study. in NA Stanton, S Landry, G Di Bucchianico & A Vallicelli (eds), Advances in Human Aspects of Transportation : Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation. vol. 484, Advances in Intelligent Systems and Computing, vol. 484, Springer, Cham, Switzerland, pp. 1151-1164, 7 th International Conference on Human Factors in Transportation, Orlando, Florida, United States, 27/07/16. https://doi.org/10.1007/978-3-319-41682-3_94

Towards a real-time driver workload estimator: An on-the-road study. / Van Leeuwen, Peter; Landman, Renske; Buning, Lejo et al.
Advances in Human Aspects of Transportation : Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation. ed. / Neville A. Stanton; Steven Landry; Giuseppe Di Bucchianico; Andrea Vallicelli. Vol. 484 Cham, Switzerland: Springer, 2016. p. 1151-1164 (Advances in Intelligent Systems and Computing; Vol. 484).

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

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AU - Heffelaar, Tobias

AU - Hogema, Jeroen

AU - van Hemert, Jasper Michiel

AU - de Winter, Joost

AU - Happee, Riender

N1 - 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.

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AB - Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driver’s workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.

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PB - Springer

CY - Cham, Switzerland

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ER -

Van Leeuwen P, Landman R, Buning L, Heffelaar T, Hogema J, van Hemert JM et al. Towards a real-time driver workload estimator: An on-the-road study. In Stanton NA, Landry S, Di Bucchianico G, Vallicelli A, editors, Advances in Human Aspects of Transportation : Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation. Vol. 484. Cham, Switzerland: Springer. 2016. p. 1151-1164. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-41682-3_94

Towards a real-time driver workload estimator: An on-the-road study

Abstract

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Keywords

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