Abstract
The use of in-vehicle information systems has increased in the past years. These systems assist the user but can as well cause additional cognitive load. The study presented in this paper was carried out to enable workload estimation in order to adapt information and entertainment systems so that an optimal driver performance and user experience is ensured. For this purpose smartphone sensor data, situational factors and basic user characteristics are taken into account. The study revealed that the driving situation, the gender of the user and the frequency of driving significantly influence the user’s workload. Using only this information and smartphone sensor data the current workload of the driver can be estimated with 86% accuracy.
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Biermann, A., Eick, E.M., Brünken, R., Debus, G., Leutner, D.: Development and first evaluation of a prediction model for risk of offences and accident involvement among young drivers. Driver Behaviour and Training 2, 169–178 (2005)
Brooke, J.: SUS - A quick and dirty usability scale. Redhatch Consulting, United Kingdom (2011)
Bubb, H.: Fahrerassistenz primär ein beitrag zum komfort oder für die sicherheit? VDI-Berichte, pp. 25–44 (2003)
Cain, B.: A review of the mental workload literature. Tech. rep., DTIC Document (2007)
Cherri, C., Nodari, E., Toffetti, A.: Review of existing tools and methods. Tech. rep., AIDE Deliverable D2.1.1 (2004)
Csikszentmihalyi, M.: FLOW. Das Geheimnis des Glücks. Klett-Cotta, Stuttgart (2008)
Eggemeier, F., Wilson, G., Kramer, A., Damos, D.: Workload assessment in multi-task environments. In: Damos, D. (ed.) Multiple Task Performance, pp. 207–216. Taylor & Francis, London (1991)
Fuller, R.: The task-capability interface model of the driving process. Recherche-Transports-Sécurité 66, 47–57 (2000)
Fuller, R.: Towards a general theory of driver behaviour. Accident Analysis & Prevention 37(3), 461–472 (2005)
Gaczek, D.: Entwurf und Regelung eines Verbrauchsassistenten. GRIN Verlag (2009)
Gopher, D., Donchin, E.: Workload - an examination of the concept. In: Boff, K., Kaufman, L., Thomas, J. (eds.) Handbook of Perception and Human Performance. Cognitive Processes and Performance, vol. 2, pp. . 41:1–41:49. Wiley, New York (1986)
Hale, A., Stoop, J., Hommels, J.: Human error models as predictors of accident scenarios for designers in road transport systems. Ergonomics 33(10-11), 1377–1387 (1990)
Hart, S.G., Staveland, L.E.: Development of nasa-tlx (task load index): Results of empirical and theoretical research. Human Mental Workload 1(3), 139–183 (1988)
Jex, H.R.: Measuring mental workload: Problems, progress, and promises. Advances in Psychology 52, 5–39 (1988)
Lysaght, R.J., Hill, S.G., Dick, A., Plamondon, B.D., Linton, P.M.: Operator workload: Comprehensive review and evaluation of operator workload methodologies. Tech. rep., DTIC Document (1989)
Ma, R., Kaber, D.B.: Situation awareness and workload in driving while using adaptive cruise control and a cell phone. International Journal of Industrial Ergonomics 35(10), 939–953 (2005)
Matthews, R., Legg, S., Charlton, S.: The effect of cell phone type on drivers subjective workload during concurrent driving and conversing. Accident Analysis & Prevention 35(4), 451–457 (2003)
Mayser, C., Ebersbach, D., Dietze, M., Lippold, C.: Fahrerassistenzsysteme zur unterstützung der längsregelung im ungebundenen verkehr. In: Conference Aktive Sicherheit durch Fahrerassistenz (2004)
Michon, J.A.: A critical view of driver behavior models: what do we know, what should we do? Springer (1986)
Oron-Gilad, T., Ronen, A., Shinar, D.: Alertness maintaining tasks (amts) while driving. Accident Analysis & Prevention 40(3), 851–860 (2008)
Pauzié, A.: Evaluating driver mental workload using the driving activity load index (dali). In: Proc. of European Conference on Human Interface Design for Intelligent Transport Systems, pp. 67–77 (2008)
Pauzié, A., Manzano, J.: Evaluation of driver mental workload facing new in-vehicle information and communication technology. In: Proceedings of the 20th Enhanced Safety of Vehicles Conference (ESV20), Lyon, France, vol. 10 (2007)
Recarte, M.A., Nunes, L.M.: Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology Applied 9(2), 119–133 (2003)
Schweitzer, J., Green, P.: Task acceptability and workload of driving city streets, rural roads, and expressways: Ratings from video clips (2007)
Taubman-Ben-Ari, O., Mikulincer, M., Gillath, O.: The multidimensional driving style inventory scale construct and validation. Accident Analysis & Prevention 36(3), 323–332 (2004)
Tsimhoni, O., Green, P.: Visual demand of driving and the execution of display-intensive in-vehicle tasks. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 45, pp. 1586–1590. SAGE Publications (2001)
Verwey, W.B.: On-line driver workload estimation. effects of road situation and age on secondary task measures. Ergonomics 43(2), 187–209 (2000)
de Waard, D.: The measurement of drivers’ mental workload. Groningen University, Traffic Research Center (1996)
Wundersitz, L., Burns, N.: Identifying young driver subtypes: relationship to risky driving and crash involvement. Driver Behaviour And Training 2, 155 (2005)
Zeitlin, L.R.: Micromodel for objective estimation of driver mental workload from task data. Transportation Research Record: Journal of the Transportation Research Board 1631(1), 28–34 (1998)
Zhang, Y., Owechko, Y., Zhang, J.: Learning-based driver workload estimation. In: Prokhorov, D. (ed.) Computational Intelligence in Automotive Applications. SCI, vol. 132, pp. 1–17. Springer, Heidelberg (2008)
Zijstra, C., Doorn, R.V.: The construction of a scale to measure perceived effort. Tech. rep., Department of Philosophy and Social Sciences, Delft University of Technology (1985)
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Ohm, C., Ludwig, B. (2013). Estimating the Driver’s Workload. In: Timm, I.J., Thimm, M. (eds) KI 2013: Advances in Artificial Intelligence. KI 2013. Lecture Notes in Computer Science(), vol 8077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40942-4_12
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DOI: https://doi.org/10.1007/978-3-642-40942-4_12
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