Abstract
Multitasking has become surprisingly present in our life. This is mostly due to the fact that nowadays most of our activities involve the interaction with one or more devices. In such a context the brain mechanism of selective attention plays a key role in determining the success of a human’s interaction with a device. Indeed, it is a resource to be shared among the concurrent tasks to be performed, and the sharing of attention turns out to be a process similar to process scheduling in operating systems. In order to study human multitasking situations in which a user interacts with more than one device at the same time, we proposed in a previous work an algorithm for simulating human selective attention. Our algorithm focuses, in particular, on safety-critical human multitasking, namely situations in which some of the tasks the user is involved in may lead to dangerous consequences if not executed properly. In this paper, we present the validation of such an algorithm against data gathered from an experimental study performed with real users involved concurrently in a “main” task perceived as safety-critical and in a series of “distractor” tasks having different levels of cognitive load.
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Notes
- 1.
Available at http://pages.di.unipi.it/milazzo/AppSpans/.
- 2.
Available at http://pages.di.unipi.it/milazzo/AppSpans2/.
References
Anderson, J.R., Matessa, M., Lebiere, C.: ACT-R: a theory of higher level cognition and its relation to visual attention. Hum. Comput. Interact. 12(4), 439–462 (1997)
Barrouillet, P., Camos, V.: The time-based resource-sharing model of working memory. Cogn. Neurosci. Work. Mem. 455, 59–80 (2007)
Broccia, G., Milazzo, P., Ölveczky, P.C.: An algorithm for simulating human selective attention. In: Cerone, A., Roveri, M. (eds.) SEFM 2017. LNCS, vol. 10729, pp. 48–55. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-74781-1_4
Broccia, G., Milazzo, P., Ölveczky, P.C.: An executable formal framework for safety-critical human multitasking. In: Dutle, A., Muñoz, C., Narkawicz, A. (eds.) NFM 2018. LNCS, vol. 10811, pp. 54–69. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-77935-5_4
Broccia, G.: A formal framework for modelling and analysing safety-critical human multitasking. Ph.D. Thesis. University of Pisa, Department of Computer Science (2019)
Broccia, G., Milazzo, P., Ölveczky, P. C. Formal modeling and analysis of safety-critical human multitasking. Innov. Syst. Softw. Eng., 1–22 (2019)
Dangerous distraction: Safety Investigation Report B2004/0324. Australian Transport Safety Bureau (2005). https://www.atsb.gov.au/media/36244/distraction_report.pdf
Case, R., Kurland, D.M., Goldberg, J.: Operational efficiency and the growth of short-term memory span. J. Exp. Child Psychol. 33(3), 386–404 (1982)
Cerone, A.: A cognitive framework based on rewriting logic for the analysis of interactive systems. In: De Nicola, R., Kühn, E. (eds.) SEFM 2016. LNCS, vol. 9763, pp. 287–303. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41591-8_20
Clark, T., David, Y.: Impact of clinical alarms on patient safety. American College of Clinical Engineering Healthcare Technology Foundation Web site (2009)
Conway, A.R.A., Cowan, N., Bunting, M.F., Therriault, D.J., Minkoff, S.R.B.: A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence 30(2), 163–183 (2002)
Conway, A.R.A., Kane, M.J., Engle, R.W.: Working memory capacity and its relation to general intelligence. Trends Cogn. Sci. 7(12), 547–552 (2003)
Conway, A.R.A., Kane, M.J., Bunting, M.F., Hambrick, D.Z., Wilhelm, O., Engle, R.W.: Working memory span tasks: a methodological review and user’s guide. Psychon. Bull. Rev. 12(5), 769–786 (2005). https://doi.org/10.3758/BF03196772
Daneman, M., Carpenter, P.A.: Individual differences in working memory and reading. J. Verbal Learn. Verbal Behav. 19(4), 450–466 (1980)
de Fockert, J.W., Rees, G., Frith, C.D., Lavie, N.: The role of working memory in visual selective attention. Science 291(5509), 1803–1806 (2001)
Dingus, T.A., Guo, F., Lee, S., Antin, J.F., Perez, M., Buchanan-King, M., Hankey, J.: Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proc. Natl. Acad. Sci. 113(10), 2636–2641 (2016)
Engle, R.W., Tuholski, S.W., Laughlin, J.E., Conway, A.R.A.: Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. J. Exp. Psychol. Gen. 128(3), 309 (1999)
Engle, R.W.: Working memory capacity as executive attention. Curr. Dir. Psychol. Sci. 11(1), 19–23 (2002)
Gelman, G., Feigh, K.M., Rushby, J.M.: Example of a complementary use of model checking and human performance simulation. IEEE Trans. Hum. Mach. Syst. 44(5), 576–590 (2014)
Hamilton, J.: Think you’re multitasking? Think again. Morning Edition (2008). https://www.npr.org/templates/story/story.php?storyId=95256794&t=1566830957675
Houser, A., Ma, L.M., Feigh, K., Bolton, M.L.: A formal approach to modeling and analyzing human taskload in simulated air traffic scenarios. In: Complex Systems Engineering (ICCSE), pp. 1–6. IEEE (2015)
Lavie, N., Hirst, A., De Fockert, J.W., Viding, E.: Load theory of selective attention and cognitive control. J. Exp. Psychol. Gen. 133(3), 339 (2004)
Mittelstädt, V., Miller, J.: Separating limits on preparation versus online processing in multitasking paradigms: evidence for resource models. J. Exp. Psychol. Hum. Percept. Perform. 43(1), 89 (2017)
Pashler, H.: Dual-task interference in simple tasks: data and theory. Psychol. Bull. 116(2), 220 (1994)
Redick, T.S., et al.: Cognitive predictors of a common multitasking ability: contributions from working memory, attention control, and fluid intelligence. J. Exp. Psychol. Gen. 145(11), 1473 (2016)
Shorrock, S.T.: Errors of memory in air traffic control. Saf. Sci. 43(8), 571–588 (2005)
Turner, M.L., Engle, R.W.: Is working memory capacity task dependent? J. Mem. Lang. 28(2), 127–154 (1989)
Wickens, C.D.: Processing resources and attention. Mult. Task Perform., 3–34 (1991)
Wickens, C.D., Gutzwiller, R.S., Santamaria, A.: Discrete task switching in overload: a meta-analyses and a model. Int. J. Hum. Comput. Stud. 79, 79–84 (2015)
Wickens, C.D., Sebok, A., Li, H., Sarter, N., Gacy, A.M.: Using modeling and simulation to predict operator performance and automation-induced complacency with robotic automation: a case study and empirical validation. Hum. Factors 57(6), 959–975 (2015)
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Broccia, G., Milazzo, P., Belviso, C., Montiel, C.B. (2020). Validation of a Simulation Algorithm for Safety-Critical Human Multitasking. In: Sekerinski, E., et al. Formal Methods. FM 2019 International Workshops. FM 2019. Lecture Notes in Computer Science(), vol 12232. Springer, Cham. https://doi.org/10.1007/978-3-030-54994-7_8
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