Skip to main content
SpringerLink
Log in

Evaluating the Impact of Passive Fatigue on Pilots Using Performance and Subjective States Measures

  • Conference paper
  • First Online:
Engineering Psychology and Cognitive Ergonomics (HCII 2023)

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

Included in the following conference series:

  • 773 Accesses

Abstract

Fatigue is a serious threat to flight safety, being a contributing factor of many aviation accidents. Sleep-related fatigue has been the most researched; however, fatigue also depends on task-related factors such as time-on-task and workload. Desmond and Hancock [1] theorized two opposite types of task-related fatigue: active fatigue (induced by cognitive overload) and passive fatigue (elicited by prolonged, understimulating and monotonous tasks). Research mainly conducted in the automotive sector demonstrated the existence of these different states and found that passive fatigue is linked to decline in performance and vigilance, together with task disengagement. Automation is extensively used in most flights, and though pilots are particularly vulnerable to passive fatigue due to the nature of their tasks (especially during cruise with autopilot engaged), no specific passive fatigue research involving pilots exist. This study intended to fill that gap, by employing well-rested licensed pilots (N = 26) who underwent an experiment involving the Multi-Attribute Task Battery (MATB) which replicates some of the tasks encountered during flight. Pilots were randomly assigned to either a one-hour very low workload scenario intended to induce passive fatigue, or a one-hour moderate workload control scenario. Pilot performance on the MATB was measured as simple reaction times (SRTs) and the frequency of missed cues on a system-monitoring task. Subjective measures were used to evaluate how task engagement and perceived workload changed over the course of the experiment. Results confirmed that passive fatigue had a detrimental effect on performance as pilots in that scenario showed significantly slower SRTs compared to the control group. Task engagement scores did not decline as predicted, but instead increased significantly more in the passive fatigue scenario, indicating a possible self-assessment inefficacy generated by the monotonous tasks. These findings suggests that wakeful pilots experience performance decline during prolonged monotonous and mostly automated flights, thus a wiser use of automation or the development of appropriate countermeasures is needed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Desmond, P.A., Hancock, P.A.: Active and passive fatigue states. In: Stress, Workload, and Fatigue, pp. 455–465. Lawrence Erlbaum Associates Publishers (2001)

    Google Scholar 

  2. Editorial, L.: Fatigue in aircraft pilots. Lancet 239(6182), 234–235 (1942). https://doi.org/10.1016/S0140-6736(00)57817-9

    Article  Google Scholar 

  3. Williamson, A., Lombardi, D.A., Folkard, S., Stutts, J., Courtney, T.K., Connor, J.L.: The link between fatigue and safety. Accid. Anal. Prev. 43(2), 498–515 (2011). https://doi.org/10.1016/j.aap.2009.11.011

    Article  Google Scholar 

  4. ICAO International Civil Aviation Organization. Doc 9966 Manual for the Oversight of Fatigue Management Approaches (2016)

    Google Scholar 

  5. Hu, X., Lodewijks, G.: Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: the value of differentiation of sleepiness and mental fatigue. J. Saf. Res. 72, 173–187 (2020). https://doi.org/10.1016/j.jsr.2019.12.015

    Article  Google Scholar 

  6. May, J.F., Baldwin, C.L.: Driver fatigue: the importance of identifying causal factors of fatigue when considering detection and countermeasure technologies. Transport. Res. F: Traffic Psychol. Behav. 12(3), 218–224 (2009). https://doi.org/10.1016/j.trf.2008.11.005

    Article  Google Scholar 

  7. Saxby, D. J. Active and Passive Fatigue in Simulated Driving (2007).http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195507547

  8. Matthews, G., Desmond, P.A.: Task-induced fatigue states and simulated driving performance. Q. J. Exp. Psychol. Sect. A 55(2), 659–686 (2002). https://doi.org/10.1080/02724980143000505

    Article  Google Scholar 

  9. Matthews, G.: Stress states, personality and cognitive functioning: a review of research with the Dundee Stress State Questionnaire. Pers. Individ. Differ. 169, 110083 (2021). https://doi.org/10.1016/j.paid.2020.110083

    Article  Google Scholar 

  10. Saxby, D.J., Matthews, G., Hitchcock, E.M., Warm, J.S.: Development of active and passive fatigue manipulations using a driving simulator. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 51, no. 18, pp. 1237–1241 (2007). https://doi.org/10.1177/154193120705101839

  11. Saxby, D.J., Matthews, G., Hitchcock, E.M., Warm, J.S., Funke, G.J., Gantzer, T.: Effect of Active and passive fatigue on performance using a driving simulator. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 52, no. 21, pp. 1751–1755. (2008). https://doi.org/10.1177/154193120805202113

  12. Matthews, G., Wohleber, R., Lin, J., Rose Panganiban, A.: Fatigue, automation, and autonomy: challenges for operator attention, effort, and trust. In Human Performance in Automated and Autonomous Systems, pp. 127–150. CRC Press (2019). https://doi.org/10.1201/9780429458330-7

  13. Thiffault, P., Bergeron, J.: Monotony of road environment and driver fatigue: a simulator study. Accid. Anal. Prev. 35(3), 381–391 (2003). https://doi.org/10.1016/S0001-4575(02)00014-3

    Article  Google Scholar 

  14. APA American Psychological Association. APA Dictionary of Psychology. https://dictionary.apa.org

  15. Matthews, G., Neubauer, C., Saxby, D.J., Wohleber, R.W., Lin, J.: Dangerous intersections? a review of studies of fatigue and distraction in the automated vehicle. Accid. Anal. Prev. 126, 85–94 (2019). https://doi.org/10.1016/j.aap.2018.04.004

    Article  Google Scholar 

  16. Schmidt, E.A., Schrauf, M., Simon, M., Fritzsche, M., Buchner, A., Kincses, W.E.: Drivers’ misjudgement of vigilance state during prolonged monotonous daytime driving. Accid. Anal. Prev. 41(5), 1087–1093 (2009). https://doi.org/10.1016/j.aap.2009.06.007

    Article  Google Scholar 

  17. Yathisha, L. Aircraft controlling system using optimal controllers. In: ATMECE (2016)

    Google Scholar 

  18. Gil, G.-H., Kaber, D., Kaufmann, K., Kim, S.-H.: Effects of modes of cockpit automation on pilot performance and workload in a next generation flight concept of operation. Hum. Fact. Ergon. Manuf. Serv. Ind. 22(5), 395–406 (2012). https://doi.org/10.1002/hfm.20377

    Article  Google Scholar 

  19. Berry, D.: How long do pilots really spend on autopilot? (2018).https://saiblog.cranfield.ac.uk/blog/how-long-do-pilots-really-spend-on-autopilot

  20. Dietrich, A.M.: Unsettled Topics in the General Aviation Autonomy Landscape (2022). https://doi.org/10.4271/EPR2022004

  21. Wiener, E.L.: Human factors of advanced technology (glass cockpit) transport aircraft (1989)

    Google Scholar 

  22. Wohleber, R.W., et al.: The impact of automation reliability and operator fatigue on performance and reliance. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 60, no. 1, pp. 211–215 (2016). https://doi.org/10.1177/1541931213601047

  23. Bernhardt, K.A., Poltavski, D., Petros, T., Ferraro, F.R.: Differentiating active and passive fatigue with the use of electroencephalography. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 63, no. 1, pp. 1285–1289. (2019). https://doi.org/10.1177/1071181319631106

  24. Farahmand, B., Boroujerdian, A.M.: Effect of road geometry on driver fatigue in monotonous environments: a simulator study. Transport. Res. F: Traffic Psychol. Behav. 58, 640–651 (2018). https://doi.org/10.1016/j.trf.2018.06.021

    Article  Google Scholar 

  25. Wingelaar-Jagt, Y.Q., Wingelaar, T.T., Riedel, W.J., Ramaekers, J.G.: Fatigue in aviation: safety risks, preventive strategies and pharmacological interventions. Front. Physiol. 12, 1399 (2021). https://doi.org/10.3389/fphys.2021.712628

    Article  Google Scholar 

  26. Cegarra, J., Valéry, B., Avril, E., Calmettes, C., Navarro, J.: OpenMATB: a multi-attribute task battery promoting task customization, software extensibility and experiment replicability. Behav. Res. Methods 52(5), 1980–1990 (2020). https://doi.org/10.3758/s13428-020-01364-w

    Article  Google Scholar 

  27. Larue, G.S., Rakotonirainy, A., Pettitt, A.N.: Predicting driver’s hypovigilance on monotonous roads: literature review. In: 1st International Conference on Driver Distraction and Inattention (2010)

    Google Scholar 

  28. Helton, W.S.: Validation of a short stress state questionnaire. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 48, no. 11, pp. 1238–1242 (2004). https://doi.org/10.1177/154193120404801107

  29. Helton, W.S., Näswall, K.: Short stress state questionnaire. Eur. J. Psychol. Assess. 31(1), 20–30 (2015). https://doi.org/10.1027/1015-5759/a000200

    Article  Google Scholar 

  30. Hart, S.G., Staveland, L.E. Development of NASA-TLX (Task Load Index): results of empirical and theoretical research, pp. 139–183 (1988). https://doi.org/10.1016/S0166-4115(08)62386-9

  31. Miller, S.: Workload Measures Literature Review. National Advanced Driving Simulator University of Iowa (2001)

    Google Scholar 

  32. Bergum, B.O., Lehr, D.J.: End spurt in vigilance. J. Exp. Psychol. 66(4), 383–385 (1963). https://doi.org/10.1037/h0044865

    Article  Google Scholar 

  33. Belz, S.M., Robinson, G.S., Casali, J.G.: Temporal separation and self-rating of alertness as indicators of driver fatigue in commercial motor vehicle operators. Hum. Fact. J. Hum. Fact. Ergon. Soc. 46(1), 154–169 (2004). https://doi.org/10.1518/hfes.46.1.154.30393

    Article  Google Scholar 

  34. Caldwell, J.A., Caldwell, J.L., Brown, D.L., Smith, J.K.: The effects of 37 hours of continuous wakefulness on the physiological arousal, cognitive performance, self-reported mood, and simulator flight performance of F-117A pilots. Mil. Psychol. 16(3), 163–181 (2004). https://doi.org/10.1207/s15327876mp1603_2

    Article  Google Scholar 

Download references

Acknowledgments

Special thanks to the Coventry University’s Human Factors in Aviation MSc academic staff that helped in the realization of this research. Words cannot express our gratitude to all the kind and patient people that helped through the long and complicated process of reaching potential pilot participants and arranging the experiment with them. We would like to particularly thank Marco Frosio, Elena Guardigli, Stefano ‘Steve’ Caini, Cristian Groff, Pietro Luigi Rinaldi and Damiano Fachiri as this endeavor would not have been feasible without all of you. We would like to extend my sincere thanks to all the staff of Professional Aviation S.r.l., FTO Padova S.r.l. and Aeroclub Ferrara flight schools as well as DastyFlySim Simulation Centre for promoting this research and for offering unrestricted use of their facilities for the experimental needs. Finally, we would like to express our deepest appreciation to all the 26 pilots who took part in the experiment and spent hours of their valuable time to help us out in this project.

Author information

Authors and Affiliations

  1. Faculty of Engineering, Environment and Computing, Coventry University, Coventry, CV1 5FB, UK

    Stefano Conte & Donald Harris

  2. Institute of Clean Growth and Future Mobility, Coventry University, Coventry, CV1 5FB, UK

    James Blundell

Authors
  1. Stefano Conte
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Donald Harris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. James Blundell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stefano Conte .

Editor information

Editors and Affiliations

  1. Coventry University, Coventry, UK

    Don Harris

  2. Cranfield University, Cranfield, UK

    Wen-Chin Li

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Conte, S., Harris, D., Blundell, J. (2023). Evaluating the Impact of Passive Fatigue on Pilots Using Performance and Subjective States Measures. 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_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-35392-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35391-8

  • Online ISBN: 978-3-031-35392-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation