research-article

Exploring the effects of visual cognitive load and illumination on pupil diameter in driving simulators

Authors:

Oskar Palinko,

Andrew L. KunAuthors Info & Claims

ETRA '12: Proceedings of the Symposium on Eye Tracking Research and Applications

Pages 413 - 416

https://doi.org/10.1145/2168556.2168650

Published: 28 March 2012 Publication History

Get Access

Abstract

Pupil diameter is an important measure of cognitive load. However, pupil diameter is also influenced by the amount of light reaching the retina. In this study we explore the interaction between these two effects in a simulated driving environment. Our results indicate that it is possible to separate the effects of illumination and visual cognitive load on pupil diameter, at least in certain situations.

References

[1]

Bailey B. P., and Iqbal S. T. 2008. Understanding changes in mental workload during execution of goal-directed tasks and its application for interruption management. ACM Transactions on Computer-Human Interaction. 14(4):1--28.

Digital Library

Google Scholar

[2]

Beatty, J. 1982. Task-Evoked Pupillary Responses, Processing Load, and the Structure of Processing Resources. Psychological Bulletin. 91(2).276--292.

Crossref

Google Scholar

[3]

Coughlin, J. F., Reimer, B., and Mehler, B. 2011. Monitoring, Managing and Motivating Driver Safety and Well-Being. IEEE Pervasive Computing. 10(3), 14--21.

Digital Library

Google Scholar

[4]

Klingner, J., Kumar, R., and Hanrahan, P. 2008. Measuring the Task-Evoked Pupillary Response with a Remote Eye Tracker. Proceedings of Eye Tracking Research and Applications.

Digital Library

Google Scholar

[5]

Palinko, O., Kun, A. L., Shyrokov, A., and Heeman, P. 2010. Estimating Cognitive Load Using Remote Eye Tracking in a Driving Simulator. Proceedings of Eye Tracking Research and Applications.

Digital Library

Google Scholar

[6]

Palinko, O., and Kun. 2011. Exploring the Influence of Light and Cognitive Load on Pupil Diameter in Driving Simulator Studies. Proceedings of Driving Assessment.

Crossref

Google Scholar

[7]

Pomplun, M., and Sunkara, S. 2003. Pupil Dilation as an Indicator of Cognitive Workload in Human-Computer Interaction. Proceedings of the International Conference on HCI.

Google Scholar

[8]

Recarte, M. A., and Nunes, L. M. 2000. Effects of verbal and spatial-imagery tasks on eye fixations while driving. Journal of Experimental Psychology. 6(1): 31--43.

Google Scholar

[9]

Wickens C. D. 2002. Multiple Resources and Performance Prediction. Theoretical Issues in Ergonomic Science. 3: 2.159--177.

Crossref

Google Scholar

Cited By

View all

Foltyn ADeuschel JLang-Richter NHolzer NOppelt M(2024)Evaluating the robustness of multimodal task load estimation modelsFrontiers in Computer Science10.3389/fcomp.2024.13711816Online publication date: 10-Apr-2024
https://doi.org/10.3389/fcomp.2024.1371181
Lee Jde Jong NDonkers JJarodzka Hvan Merriënboer J(2024)Measuring Cognitive Load in Virtual Reality Training via PupillometryIEEE Transactions on Learning Technologies10.1109/TLT.2023.332647317(704-710)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TLT.2023.3326473
Li MZhang CXiang W(2024)Feedback or Takeover: The Impact of Risk and Driver State on Intervention Behaviors in Automated Driving2024 16th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)10.1109/IHMSC62065.2024.00051(192-196)Online publication date: 24-Aug-2024
https://doi.org/10.1109/IHMSC62065.2024.00051
Show More Cited By

Index Terms

Exploring the effects of visual cognitive load and illumination on pupil diameter in driving simulators
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Estimating cognitive load using remote eye tracking in a driving simulator
ETRA '10: Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications

We report on the results of a study in which pairs of subjects were involved in spoken dialogues and one of the subjects also operated a simulated vehicle. We estimated the driver's cognitive load based on pupil size measurements from a remote eye ...
Measuring the task-evoked pupillary response with a remote eye tracker
ETRA '08: Proceedings of the 2008 symposium on Eye tracking research & applications

The pupil-measuring capability of video eye trackers can detect the task-evoked pupillary response: subtle changes in pupil size which indicate cognitive load. We performed several experiments to measure cognitive load using a remote video eye tracker, ...
Measuring Cognitive Load using Eye Tracking Technology in Visual Computing
BELIV '16: Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization

In this position paper we encourage the use of eye tracking measurements to investigate users' cognitive load while interacting with a system. We start with an overview of how eye movements can be interpreted to provide insight about cognitive processes ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ETRA '12: Proceedings of the Symposium on Eye Tracking Research and Applications

March 2012

420 pages

ISBN:9781450312219

DOI:10.1145/2168556

Conference Chairs:
Carlos H. Morimoto
University of São Paulo, Brazil
,
Howell Istance
Montfort University, UK
,
Editor:
Stephen N. Spencer
University of Washington
,
Program Chairs:
Jeffrey B. Mulligan
NASA
,
Pernilla Qvarfordt
FX Palo Alto

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

U.S. Department of Justice

Conference

ETRA '12

Sponsor:

ETRA '12: Eye Tracking Research and Applications

March 28 - 30, 2012

California, Santa Barbara

Acceptance Rates

Overall Acceptance Rate 69 of 137 submissions, 50%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

35
Total Citations
View Citations
559
Total Downloads

Downloads (Last 12 months)32
Downloads (Last 6 weeks)2

Reflects downloads up to 21 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Foltyn ADeuschel JLang-Richter NHolzer NOppelt M(2024)Evaluating the robustness of multimodal task load estimation modelsFrontiers in Computer Science10.3389/fcomp.2024.13711816Online publication date: 10-Apr-2024
https://doi.org/10.3389/fcomp.2024.1371181
Lee Jde Jong NDonkers JJarodzka Hvan Merriënboer J(2024)Measuring Cognitive Load in Virtual Reality Training via PupillometryIEEE Transactions on Learning Technologies10.1109/TLT.2023.332647317(704-710)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TLT.2023.3326473
Li MZhang CXiang W(2024)Feedback or Takeover: The Impact of Risk and Driver State on Intervention Behaviors in Automated Driving2024 16th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)10.1109/IHMSC62065.2024.00051(192-196)Online publication date: 24-Aug-2024
https://doi.org/10.1109/IHMSC62065.2024.00051
Yu MChen JQian JYuan QFan HShan G(2024)Effects of color temperature and time gradients on visual fatigue recovery in closed cabinAdvanced Design Research10.1016/j.ijadr.2024.07.0022:1(45-54)Online publication date: Jun-2024
https://doi.org/10.1016/j.ijadr.2024.07.002
Nagy VKovács GFöldesi PKurhan DSysyn MSzalai SFischer S(2023)Testing Road Vehicle User Interfaces Concerning the Driver’s Cognitive LoadInfrastructures10.3390/infrastructures80300498:3(49)Online publication date: 9-Mar-2023
https://doi.org/10.3390/infrastructures8030049
Kosch TKarolus JZagermann JReiterer HSchmidt AWoźniak P(2023)A Survey on Measuring Cognitive Workload in Human-Computer InteractionACM Computing Surveys10.1145/358227255:13s(1-39)Online publication date: 13-Jul-2023
https://dl.acm.org/doi/10.1145/3582272
Bacchin DGehrer NKrejtz KDuchowski AGamberini L(2023)Gaze-based Metrics of Cognitive Load in a Conjunctive Visual Memory TaskExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585650(1-8)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585650
Luo RWeng YJayakumar PBrudnak MPaul VDesaraju VStein JErsal TYang X(2023)Real-Time Workload Estimation Using Eye Tracking: A Bayesian Inference ApproachInternational Journal of Human–Computer Interaction10.1080/10447318.2023.220527440:15(4042-4057)Online publication date: 4-May-2023
https://doi.org/10.1080/10447318.2023.2205274
Aygun ANguyen THaga ZAeron SScheutz M(2022)Investigating Methods for Cognitive Workload Estimation for Assistive RobotsSensors10.3390/s2218683422:18(6834)Online publication date: 9-Sep-2022
https://doi.org/10.3390/s22186834
Aygun ALyu BNguyen THaga ZAeron SScheutz M(2022)Cognitive Workload Assessment via Eye Gaze and EEG in an Interactive Multi-Modal Driving TaskProceedings of the 2022 International Conference on Multimodal Interaction10.1145/3536221.3556610(337-348)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3536221.3556610
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Estimating cognitive load using remote eye tracking in a driving simulator

Measuring the task-evoked pupillary response with a remote eye tracker

Measuring Cognitive Load using Eye Tracking Technology in Visual Computing