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A Comparison of Subjective Mental Workload Measures in Driving Contexts

  • Kim, Ji Yeon (Department of Information & Industrial Engineering, Yonsei University) ;
  • Ji, Yong Gu (Department of Information & Industrial Engineering, Yonsei University)
  • 투고 : 2012.09.23
  • 심사 : 2013.03.11
  • 발행 : 2013.04.30

초록

Objective: This study aims to compare the usefulness of subjective measures which are comprised of existing methods like NASA-TLX, Bedford-scale and ZEIS and newly developed method like DALI in measuring drivers' mental workload in terms of validity, sensitivity and diagnosticity. Background: Nowadays, with the development of intelligent vehicle and HMI, mental workload of driver has become more and more important. For this reason, the studies on drivers' mental workload about driving situation and the use of information technology equipment such as mobile phones and navigations were conducted intensively. However, the studies on measuring drivers' mental workload were rarely conducted. Moreover, most of studies on comparison of subjective measures were used with performance based measure. However, performance based measures can cause distraction effect with subjective measures. Method: Participants (N=19) were engaged in a driving simulation experiment in 2 driving contexts (downtown driving and highway driving context). The experiment has 2 sessions according to driving contexts. The level of difficulties by driving contexts were adjusted according to existence of intersections, traffic signs and signals, billboards and the number of doublings. Moreover, as criteria of concurrent validity and sensitivity, the EEG data were recorded before and during the sessions. Results: The results indicated that all subjective methods were correlates with EEG in high-way driving. On the contrary to this, in downtown driving, all subjective methods were not correlates with EEG. In terms of sensitivity, multi-dimensional scales (NASA-TLX, DALI) were the only ones to identify differences between high way and downtown driving. Finally, in terms of diagnosticity, DALI was the most suitable method for evaluating drivers' mental workload in driving context. Conclusion: The DALI as newly developed method dedicated to evaluate driver's mental workload was superior in terms of sensitivity and diagnosticity. However, researchers should consider the characteristics of each subjective method synthetically according to research objective by selecting the method in subjective measures. Application: The results of this study could be applied to the intelligent vehicle and next generation of HMI design to decrease mental workload of driver and for the development of new subjective method in vehicle domain.

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참고문헌

  1. Brookings, J.B., Wilson, G.F. & Swain, C.R., Psychophysiological responses to changes in workload during simulated air traffic control, Biological Psychology, 42(3), 361-377, 1996. https://doi.org/10.1016/0301-0511(95)05167-8
  2. Cantin, V., Lavalliere, M., Simoneau, M. & Teasdale, N., Mental workload when driving in a simulator: Effects of age and driving complexity, Accident Analysis & Prevention, 41(4), 763-771, 2009. https://doi.org/10.1016/j.aap.2009.03.019
  3. Chin, E., Nathan, F., Pauzie, A., Manzano, J., Nodari, E., Cherri, C, et al. Subjective Assessment methods for Workload. http://www.aide-eu.org/ pdf/sp2_deliv_new/aide_d2_2_6.pdf, 2004.
  4. De Waard, D., The measurement of Driver's Mental workload. Ph.D. Thesis. University of Groningen. Traffic research center. Haren, The Netherlands, 1996.
  5. Doyle, M.J., Psychophysiological correlates of cognitive workload during a satellite management decision-training task. In proceedings of Human Systems Integration Symposium, Annapolis, Maryland, http:// navalengineers.net/Proceedings/HSIS2009/Index.html, 2007.
  6. Eggemeier, F.T., Wilson, G.F., Kramer, A.F. & Damos, DL., General considerations concerning workload assessment in multi-task environments. Taylor & Francis, London, 1991.
  7. Hill, S.G., Iavecchia, H.P., Byers, J.C., Bittner, A.C., Byers, J.C., Zaklade, A.L. & Christ, R.E., Comparison of Four Subjective Workload Rating Scales. Human Factors: The Journal of the Human Factors and Ergonomics Society, 34(4), 429-439, 1992. https://doi.org/10.1177/001872089203400405
  8. Horberry, T., Anderson, J., Regan, M.A., Triggs, T.J. & Brown, J., Driver distraction: The effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance, Accident Analysis & Prevention, 38(1), 185-191, 2006. https://doi.org/10.1016/j.aap.2005.09.007
  9. Lei, S. & Roetting, M., Influence of Task Combination on EEG Spectrum Modulation for Driver Workload Estimation, Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(2), 168-179, 2011. https://doi.org/10.1177/0018720811400601
  10. 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. https://doi.org/10.1016/S0001-4575(02)00023-4
  11. Miller, S., LITERATURE REVEIW Workload Measures. http://www.nads-sc.uiowa.edu/publicationStorage/200501251347060.N01-006.pdf, 2001.
  12. Patten, C.J.D., Kircher, A., Östlund, J. & Nilsson, L., Using mobile telephones: cognitive workload and attention resource allocation, Accident Analysis & Prevention, 36(3), 341-350, 2004. https://doi.org/10.1016/S0001-4575(03)00014-9
  13. Patten, C.J.D., Kircher, A., Ostlund, J., Nilsson, L. & Svenson, O., Driver experience and cognitive workload in different traffic environments, Accident Analysis & Prevention, 38(5), 887-894, 2006. https://doi.org/10.1016/j.aap.2006.02.014
  14. Pauzie, A., A method to assess the driver mental workload: The driving activity load index (DALI), IET Intelligent Transport Systems, 2(4), 315-322, 2008. https://doi.org/10.1049/iet-its:20080023
  15. Rouse, W.B., Edwards, S.L. & Hammer, J.M., Modeling the dynamics of mental workload and human performance in complex systems, Systems, Man and Cybernetics, 23(6), 1662-1671, 1993. https://doi.org/10.1109/21.257761
  16. Rubio, S., Díaz, E., Martín, J. & Puente, J.M., Evaluation of Subjective Mental Workload: A Comparison of SWAT, NASA-TLX, and Workload Profile Methods, Applied Psychology, 53(1), 61-86, 2004. https://doi.org/10.1111/j.1464-0597.2004.00161.x
  17. Ryu, K. & Myung, R., Evaluation of mental workload with a combined measure based on physiological indices during a dual task of tracking and mental arithmetic, International Journal of Industrial Ergonomics, 35(11), 991-1009, 2005. https://doi.org/10.1016/j.ergon.2005.04.005
  18. Sterman, M.B., Mann, C.A., Kaiser, D.A. & Suyenobu, B.Y., Multiband topographic EEG analysis of a simulated visuomotor aviation task, International Journal of Psychophysiology, 16(1), 49-56, 1994. https://doi.org/10.1016/0167-8760(94)90041-8
  19. Teasdale, N., Cantin, V., Blouin, J. & Simoneau, M., Attentional demands while driving in a simulator: effects of driving straights on open roads, approaching intersections and doubling maneuvers, Advances in Transportation Studies an international Journal, 2004 Special issue, 75-84, 2004.
  20. Valentino, D.A., Arruda, J.E. & Gold, S.M., Comparison of QEEG and response accuracy in good vs poorer performers during a vigilance task, International Journal of Psychophysiology, 15(2), 123-133, 1993. https://doi.org/10.1016/0167-8760(93)90070-6
  21. Verwey, W.B., How can we prevent overload of the driver?, in: Parkes, A.M., S.Franzen. (Eds.), Driving future vehicles. Taylor&Francis, London, pp. 235-244, 1993.
  22. Yeh, Y.-Y. & Wickens, C.D., Dissociation of Performance and Subjective Measures of Workload, Human Factors: The Journal of the Human Factors and Ergonomics Society, 30(1), 111-120, 1988. https://doi.org/10.1177/001872088803000110