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A Comparison of Subjective Mental Workload Measures in Driving Contexts

대한인간공학회지 제32권 제2호, 2013.4, 167-177 (11 pages)
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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.

목차
ABSTRACT
1. Introduction
2. Method
3. Results
4. Discussion
5. Conclusion
References
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  1. Brookings, J.B. , 1996 , Psychophysiological responses to changes in workload during simulated air traffic control , Biological Psychology 42 (3) : 361 ~ 377

  2. Cantin, V. , 2009 , Mental workload when driving in a simulator: Effects of age and driving complexity , Accident Analysis & Prevention 41 (4) : 763 ~ 771

  3. Chin, E. , , Subjective Assessment methods for Workload

  4. De Waard, D. , 1996 , The measurement of Driver's Mental workload , 박사 , University of Groningen

  5. Doyle, M.J. , , Psychophysiological correlates of cognitive workload during a satellite management decision-training task. In proceedings of Human Systems Integration Symposium

  6. Eggemeier, F.T. , 1991 , General considerations concerning workload assessment in multi-task environments , Taylor & Francis

  7. Hill, S. G. , 1992 , Comparison of Four Subjective Workload Rating Scales , Human Factors: The Journal of the Human Factors and Ergonomics Society 34 (4) : 429 ~ 439

  8. Horberry, T. , 2006 , Driver distraction: The effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance , Accident Analysis & Prevention 38 (1) : 185 ~ 191

  9. Lei, S. , 2011 , 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

  10. Matthews, R. , 2003 , The effect of cell phone type on drivers subjective workload during concurrent driving and conversing , Accident Analysis & Prevention 35 (4) : 451 ~ 457

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