Objective: This study tested whether the ease of learning to use human—machine interfaces of in-vehicle information systems (IVIS) can be assessed at standstill. Background: Assessing the attentional demand of IVIS should include an evaluation of ease of learning, because the use of IVIS at low skill levels may create safety-relevant distractions. Method: Skill acquisition in operating IVIS was quantified by fitting the power law of practice to training data sets collected in a driving study and at standstill. Participants practiced manual destination entry with two route guidance systems differing in cognitive demand. In Experiment 1, a sample of middle-aged participants was trained while steering routes of varying driving demands. In Experiment 2, another sample of middle-aged participants was trained at standstill. Results: In Experiment 1, display glance times were less affected by driving demands than by total task times and decreased at slightly higher speed-up rates (0.02 higher on average) than task times collected at standstill in Experiment 2. The system interface that minimized cognitive demand was operated more quickly and was easier to learn. Its system delays increased static task times, which still predicted 58% of variance in display glance times compared with even 76% for the second system. Conclusion: The ease of learning to use an IVIS interface and the decrease in attentional demand with training can be assessed at standstill. Application: Fitting the power law of practice to static task times yields parameters that predict display glance times while driving, which makes it possible to compare interfaces with regard to ease of learning.
Bainbridge, L., & Quintanilla, R. (Eds.). (1989). Developing skills with information technology. Chichester, UK: Wiley .
3.
Baumann, M., Keinath, A., Krems, J.F., & Bengler, K. (2004). Evaluation of in-vehicle HMI using occlusion techniques: Experimental results and practical implications. Applied Ergonomics , 35, 197-205.
4.
Brooke, J. (1996). SUS: A "quick and dirty" usability scale. In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189-194). London: Taylor and Francis.
5.
Burnett, G.E., Lomas, S.M., Mason, B., Porter, J.M., & Summerskill, S.J. (2005). Writing and driving: An assessment of handwriting recognition as a means of alphanumeric data entry in a driving context. Advances in Transportation Studies an International Journal, 2005 Special Issue, 59-72.
6.
Burnett, G.E., Summerskill, S.J., & Porter, J.M. (2004). On-the-move destination entry for vehicle navigation systems: Unsafe by any means? Behaviour & Information Technology, 23, 265-272.
7.
Byers, J.C., Bittner, A.C., & Hill, S.G. (1989). Traditional and raw task load index (TLX) correlations: Are paired comparisons necessary? In A. Mital (Ed.), Advances in industrial ergonomics and safety (pp. 481-485). London: Taylor and Francis.
8.
Card, S.K., English, W.K., & Burr, B. (1978). Evaluation of mouse, rate controlled isometric joystick, step keys, and text keys for text selection on a CRT. Ergonomics, 21, 601-613.
9.
Chiang, D.P., Brooks, A.M., & Weir, D.H. (2000). An experimental study of destination entry with an example automobile navigation system (SAE Paper 2001-01-0810). Warrendale, PA: Society of Automotive Engineers.
10.
Cnossen, F., Meijman, T., & Rothengatter, T. (2004). Adaptive strategy changes as a function of task demands: A study of car drivers. Ergonomics , 47, 218-236.
11.
Dingus, T.A., Hulse, M.C., Mollenhauer, M.A., Fleischman, R.N., McGehee, D.V., & Manakkal, N. (1997). Effects of age, system experience, and navigation technique on driving with an advanced traveler information system. Human Factors, 39, 177-199.
12.
European Commission. (2007). Commission recommendation of 22 December 2006 on safe and efficient in-vehicle information and communication systems: Update of the European Statement of Principles on Human Machine Interface. Official Journal of the European Union, 50L32, 200-241.
13.
Gelau, C., & Krems, J.F. (2004). The occlusion technique: A procedure to assess the HMI of in-vehicle information and communication systems. Applied Ergonomics, 35, 185-187.
14.
Gopher, D. (1992). The skill of attention control: Acquisition and execution of attention strategies. In D. E. Meyer & S. Kornblum (Eds.), Attention and performance XIV (pp. 299-322). Mahwah, NJ : Lawrence Erlbaum.
15.
Green, P. (1999). Visual and task demands of driver information systems (Technical Report UMTRI-98-16). Ann Arbor: University of Michigan, Transportation Research Institute.
16.
Haider, H., & Frensch, P.A. (2002). Why aggregated learning follows the power law of practice when individual learning does not: Comment on Rickard (1997, 1999), Delaney et al. (1998), and Palmeri (1999). Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 392-406.
17.
Hart, S.G., & Staveland, L.E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139-183). Amsterdam: Elsevier.
18.
Heathcote, A., Brown, S., & Mewhort, D.J.K. (2000). The power law repealed: The case for an exponential law of practice. Psychonomic Bulletin & Review, 7, 185-207.
19.
Horberry, T., Anderson, J., Regan, M.A., Triggs, T.J., & Brown, J. (2006). Driver distraction: The effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance . Accident Analysis & Prevention, 38, 185-191.
Jahn, G., Keinath, A., Gelau, C., & Krems, J.F. (2003). Destination entry while driving: The benefit of constrained options to act in multitask situations illustrated by two route guidance systems. In C. Stephanidis & J. Jacko (Eds.), Human-computer interaction: Theory and practice (Part 2, pp. 93-97). Mahwah, NJ: Lawrence Erlbaum.
22.
Jahn, G., Oehme, A., Krems, J.F., & Gelau, C. (2005). Peripheral detection as a workload measure in driving: Effects of traffic complexity and route guidance system use in a driving study. Transportation Research Part F, 8, 255-275.
23.
Johannson, E., Engström, J., Cherri, C., Nodari, E., Toffetti, A., Schindhelm, R., et al. (2005). Review of existing techniques and metrics for IVIS and ADAS assessment (Deliverable No. D2.1.1). Adaptive Integrated Driver-vehicle Interface (AIDE) Consortium. Retrieved from http://www.aide-eu.org/pdf/sp2_deliv_new/aide_d2_2_1.pdf
24.
Lee, J.D., Caven, B., Haake, S., & Brown, T.L. (2001). Speech-based interaction with in-vehicle computers: The effect of speech-based e-mail on drivers' attention to the road. Human Factors, 43, 631-640.
25.
Lee, J.D., & Strayer, D.L. (2004). Preface to the special section on driver distraction . Human Factors, 46, 583-586.
26.
Lee, F.J., & Anderson, J.R. (2001). Does learning a complex task have to be complex? A study in learning decomposition. Cognitive Psychology, 42, 267-316.
27.
Lee, Y.C., Lee, J.D., & Boyle, L.N. (2007). Visual attention in driving: The effects of cognitive load and visual disruption. Human Factors, 49, 721-733.
28.
Loftus, G.R. (2002). Analysis, interpretation, and visual presentation of experimental data. In H. Pashler & J. Wixted (Eds.), Stevens' handbook of experimental psychology: Vol. 4. Methodology in experimental psychology (3rd ed., pp. 339-390). New York: Wiley.
29.
Miyata, Y., & Norman, D.A. (1986). Psychological issues in support of multiple activities . In D. A. Norman & S. W. Draper (Eds.), User centered system design: New perspectives on human-computer interaction (pp. 265-284). Mahwah, NJ: Lawrence Erlbaum.
30.
Newell, A., & Rosenbloom, P. S. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1-55). Mahwah, NJ: Lawrence Erlbaum.
31.
Nowakowski, C., Utsui, Y., & Green, P. (2000). Navigation system destination entry: The effects of driver workload and input devices, and implications for SAE recommended practice (Technical Report UMTRI-2000-20). Ann Arbor: University of Michigan, Transportation Research Institute.
32.
Pashler, H., & Baylis, G.C. (1991). Procedural learning: 1. Locus of practice effects in speeded choice tasks. Journal of Experimental Psychology: Learning, Memory and Cognition, 17, 20-32.
33.
Recarte, M.A., & Nunes, L.M. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology: Applied, 9, 119-137.
34.
Ritter, F.E., & Schooler, L.J. (2001). The learning curve. In N. J. Smelser & P. B. Baltes (Eds.) International encyclopedia of the social and behavioral sciences (pp. 8602-8605). Amsterdam: Pergamon. N. J. Smelser & P. B. Baltes (Eds.)
35.
Shinar, D., Tractinsky, N., & Compton, R. (2005). Effects of practice, age, and task demands, on interference from a phone task while driving. Accident Analysis & Prevention, 37, 315-326.
36.
Singley, M.K., & Anderson, J.R. (1989). Transfer of cognitive skill. Cambridge, MA: Harvard University Press.
37.
Srinivasan, R., & Jovanis, P.P. (1997). Effect of selected in-vehicle route guidance systems on driver reaction times. Human Factors, 39, 200-215.
38.
Tijerina, L. (2001). Issues in the evaluation of driver distraction associated with in-vehicle information and telecommunications systems. EastLiberty , OH: Transportation Research Center.
39.
Tijerina, L., Johnston, S., Parmer, E., Winterbottom, M.D., & Goodman, M. (2000). Driver distraction with wireless telecommunications and route guidance systems (Technical Report DOT HS 809-069). Washington, DC: National Highway Traffic Safety Administration .
40.
Tsimhoni, O., Smith, D., & Green, P. (2004). Address entry while driving: Speech recognition versus a touch-screen keyboard. Human Factors, 46, 600-610.
41.
Wierwille, W.W., & Tijerina, L. (1998). Modelling the relationship between driver in-vehicle visual demands and accident occurrence. In A. G. Gale, I. D. Brown, C. M. Haslegrave, & S. Taylor (Eds.), Vision in vehicles VI (pp. 233-243). Amsterdam: North-Holland.
