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A Mental Workload Control Method Based on Human Performance or Safety Risk

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Engineering Psychology and Cognitive Ergonomics (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14017))

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Abstract

The prediction of mental workload, as well as the determination of its “redline”, is important in Human System Integration (HSI), as it could save time and resources by detecting problems at the early stages of system design. It is also well-recognized as a key issue in safety risk management. Till now, most of the methods in redline determination hold the perspective of a fixed and absolute threshold. However, human operators are inherently flexible and capable of adopting different strategies to maintain their task performance among a range of mental workload. In the present study, mental workload is considered as a more management than technological issue. An idea of risk-based method is proposed to determine the control line of mental workload. The concept of mental workload intensity instead of amount is proposed to establish a relationship between performance or safety risk and mental workload, so that according to the acceptable risk set by the management/administration, the mental workload control line can be determined. The idea was demonstrated with a case study of maritime tasks. The results show that the output of the proposed method is well consistent with expert judgment.

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References

  1. Matthews, G., Reinerman-Jones, L.: Workload assessment: How to diagnose workload issues and enhance performance. Human Factors and Ergonomics Society, Santa Monica, CA (2017)

    Google Scholar 

  2. Young, M.S., Brookhuis, K.A., Wickens, C.D., Hancock, P.A.: State of science: mental workload in ergonomics. Ergonomics 58(1), 1–17 (2015). https://doi.org/10.1080/00140139.2014.956151

  3. Kaber, D.B., Riley, J.M.: Adaptive automation of a dynamic control task based on secondary task workload measurement. Int. J. Cogn. Ergon. 3(3), 169–187 (2010). https://doi.org/10.1207/s15327566ijce0303_1

  4. Wickens, C.D.: Mental workload: assessment, prediction and consequences. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2017. CCIS, vol. 726, pp. 18–29. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61061-0_2

  5. Reid, G.B., Colle, H.A.: Critical SWAT values for predicting operator overloadm, 19 edn., p. 1414–8. SAGE Publications Sage CA, Los Angeles, CA (1988)

    Google Scholar 

  6. De Waard, D., Brookhuis, K.A.: The measurement of drivers’ mental workload. Groningen University, Traffic Research Center Netherlands (1996)

    Google Scholar 

  7. Hart, S., Wickens, C.D.: Mental Workload. NASA Human Integration Design Handbook (2008)

    Google Scholar 

  8. Rueb, J., Vidulich, M., Hassoun, J.: Establishing workload acceptability: An evaluation of a proposed KC-135 cockpit redesign, 1 edn., pp. 17–21.  SAGE Publications Sage CA, Los Angeles, CA (1992)

    Google Scholar 

  9. Grier, R.,  et al.: The red-line of workload: Theory, research, and design. 18 edn,  pp. 1204–8. Sage Publications Sage CA: Los Angeles, CA (2008)

    Google Scholar 

  10. Meister, D.: Behavioral foundations of system development. Behavioral foundations of system development. Oxford, England: John Wiley & Sons (1976)

    Google Scholar 

  11. Parks, D.L., Boucek, G.P.: Workload prediction, diagnosis, and continuing challenges. In: Applications of Human Performance Models to System Design, pp. 47–63. Springer  (1989). https://doi.org/10.1007/978-1-4757-9244-7_4

  12. Hancock, P.A., Warm, J.S.: A dynamic model of stress and sustained attention. Hum Factors. 31(5), 519–537 (1989). https://doi.org/10.1177/001872088903100503

    Article  Google Scholar 

  13. Smith, K.T.: Observations and issues in the application of cognitive workload modelling for decision making in complex time-critical environments, p. 77–89. Springer (2017). https://doi.org/10.1007/978-3-319-61061-0_5

  14. Byrne, A.: Mental workload as an outcome in medical education. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2017. CCIS, vol. 726, pp. 187–197. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61061-0_12

    Chapter  Google Scholar 

  15. Chen, W., Sawaragi, T., Horiguchi, Y.: Measurement of driver’s mental workload in partial autonomous driving. IFAC-PapersOnLine. 52(19), 347–352 (2019). https://doi.org/10.1016/j.ifacol.2019.12.083

    Article  Google Scholar 

  16. Das, S., Maiti, J., Krishna, O.B.: Assessing mental workload in virtual reality based EOT crane operations: A multi-measure approach. Int. J. Ind. Ergon. 80, 103017 (2020). https://doi.org/10.1016/j.ergon.2020.103017

    Article  Google Scholar 

  17. Gao, Q., Wang, Y., Song, F., Li, Z., Dong, X.: Mental workload measurement for emergency operating procedures in digital nuclear power plants. Ergonomics 56(7), 1070–1085 (2013). https://doi.org/10.1080/00140139.2013.790483

    Article  Google Scholar 

  18. Hunn, B.P., Schweitzer, K.M., Cahir, J.A., Finch, M.M.: IMPRINT analysis of an unmanned air system geospatial information process. Army Research Lab Aberdeen Proving Ground Md Human Research and Engineering (2008)

    Google Scholar 

  19. Aldrich, T.B., Szabo, S.M., Bierbaum, C.R.: The development and application of models to predict operator workload during system design. In: Applications of Human Performance Models to System Design, pp. 65–80. Springer (1989). https://doi.org/10.1007/978-1-4757-9244-7_5

  20. North, R.A., Riley, V.A.: W/INDEX: a predictive model of operator workload. In: McMillan, G.R., Beevis, D., Salas, E., Strub, M.H., Sutton, R., Van Breda, L. (eds.) Applications of Human Performance Models to System Design, pp. 81–89. Springer, US, Boston (1989). https://doi.org/10.1007/978-1-4757-9244-7_6

  21. Wickens, C.D.: Multiple resources and performance prediction. Theor. Issues Ergon. Sci. 3(2), 159–177 (2002). https://doi.org/10.1080/14639220210123806

    Article  Google Scholar 

  22. Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock, P.A., Meshkati, N. (eds.) Human Mental Workload, Advances in Psychology, pp. 139–183. North-Holland (1988)

    Google Scholar 

  23. Sellers, J., Helton, W.S., Näswall, K., Funke, G.J., Knott, B.A.: Development of the team workload questionnaire (TWLQ). Proc. Human Factors  Ergonom. Soc. Annual Meeting 58(1), 989–993 (2014). https://doi.org/10.1177/1541931214581207

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Zhang, N. et al. (2023). A Mental Workload Control Method Based on Human Performance or Safety Risk. In: Harris, D., Li, WC. (eds) Engineering Psychology and Cognitive Ergonomics. HCII 2023. Lecture Notes in Computer Science(), vol 14017. Springer, Cham. https://doi.org/10.1007/978-3-031-35392-5_13

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  • DOI: https://doi.org/10.1007/978-3-031-35392-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35391-8

  • Online ISBN: 978-3-031-35392-5

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