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Towards a Real-Time Driver Workload Estimator: An On-the-Road Study

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Advances in Human Aspects of Transportation

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 484))

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.

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Acknowledgments

We thank Menno Merts (vehicle and test equipment preparation), Arjan Stuiver, Dick Lenior (test set up/development), and Henny Wilke (test leader) for their support in the research project. The research was supported by the Netherlands Organisation for Scientific Research (NWO) of the Ministry of Education, Culture and Science through the RAAK-PRO project: “ADVICE: Advanced Driver Vehicle Interface in a Complex Environment”. RAAK-PRO focusses on the enhancement of applied scientific research by Universities of Applied Sciences, in cooperation with the industry.

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Authors and Affiliations

  1. Department of BioMechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands

    Peter van Leeuwen, Joost de Winter & Riender Happee

  2. Ergos Human Factors Engineering, Hengelosestraat 448-a, 7521 AN, Enschede, The Netherlands

    Renske Landman

  3. HAN University of Applied Sciences, Ruitenberglaan 29, 6826 CC, Arnhem, The Netherlands

    Lejo Buning

  4. Noldus Information Technology, Nieuwe Kanaal 5, 6709 PA, Wageningen, The Netherlands

    Tobias Heffelaar

  5. TNO, Perceptual and Cognitive Systems, Kampweg 5, 3769 DE, Soesterberg, The Netherlands

    Jeroen Hogema

  6. TomTom BV, Oosterdokstraat 114, 1011 DK, Amsterdam, The Netherlands

    Jasper Michiel van Hemert

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  1. Peter van Leeuwen
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  2. Renske Landman
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  3. Lejo Buning
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  4. Tobias Heffelaar
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  5. Jeroen Hogema
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  6. Jasper Michiel van Hemert
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  7. Joost de Winter
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  8. Riender Happee
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Corresponding author

Correspondence to Peter van Leeuwen .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and the Environme, University of Southampton Faculty of Engineering and the Environme, Southampton, United Kingdom

    Neville A. Stanton

  2. Purdue University , West Lafayette, IN, USA

    Steven Landry

  3. Dipartimento di Architettura, Università degli Studi “G.d’Annunzio” Chiet, Pescara, Italy

    Giuseppe Di Bucchianico

  4. Dipartimento di Architettura, Università degli Studi “G.d’Annunzio” Chiet, Pescara, Italy

    Andrea Vallicelli

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van Leeuwen, P. et al. (2017). Towards a Real-Time Driver Workload Estimator: An On-the-Road Study. In: Stanton, N., Landry, S., Di Bucchianico, G., Vallicelli, A. (eds) Advances in Human Aspects of Transportation. Advances in Intelligent Systems and Computing, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-319-41682-3_94

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  • DOI: https://doi.org/10.1007/978-3-319-41682-3_94

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41681-6

  • Online ISBN: 978-3-319-41682-3

  • eBook Packages: EngineeringEngineering (R0)

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