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The usefulness of subjective task load assessment methods for predicting pilot task load in general aviation organizations

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Języki publikacji
EN
Abstrakty
EN
Purpose: The research aimed to verify the usefulness of selected subjective methods of task load assessment for evaluating task load in general aviation organizations and forecasting pre-flight load. The study also highlighted the importance of the pilot's task load in the context of flight safety. Design/methodology/approach: The study included a comprehensive literature review to present the specifics of general aviation organization and the role of the human factor in aviation accidents. The research discussed the division of task load methods and characterized four selected subjective task load methods (NASA-TLX, SWAT, ISA, Bedford Scale). Expert assessments were conducted to evaluate these methods' effectiveness from the perspective of post-flight load assessment and pre-flight load prediction, considering the feasibility of implementation in general aviation organizations. Findings: The findings emphasized the need to develop a dedicated method for predicting task load before a flight. The study concluded that the methods used should be simple and require minimal financial outlay, considering the specificity of general aviation organizations. Research limitations/implications: Future research should focus on developing a dedicated pre-flight task load prediction method tailored to the unique requirements of general aviation. Identified limitations include the need for further validation of the subjective methods in different organizational contexts. Practical implications: The research suggests that implementing simple and cost-effective task load assessment methods can enhance flight safety in general aviation. The development of a specialized pre-flight load prediction tool could significantly improve operational planning and pilot performance. Social implications: By improving task load assessment and prediction in general aviation, the research can contribute to enhanced flight safety, thereby potentially reducing accident rates and improving public trust in aviation safety measures. Originality/value: This paper contributes to the field by addressing the gap in pre-flight task load prediction in general aviation. It provides valuable insights for aviation safety researchers, practitioners, and policymakers interested in optimizing pilot performance and ensuring flight safety.
Rocznik
Tom
Strony
19--32
Opis fizyczny
Bibliogr. 24 poz.
Twórcy
  • Poznań University of Technology, Faculty of Engineering Management, Institute of Safety and Quality Engineering
Bibliografia
  • 1. Alaimo, A., Esposito, A., Orlando, C., Simoncini, A. (2020). Aircraft Pilots Workload Analysis: Heart Rate Variability Objective Measures and NASA-Task Load Index Subjective Evaluation. Aerospace, 7(9), 137.
  • 2. Berlik, M. (2023). Metoda zarządzania ryzykiem operacyjnym na podstawie obciążenia zadaniowego pilota w bezpieczeństwie lotów (Doctoral dissertation). Poznań University of Technology.
  • 3. Berlik, M., Ewertowski, T., Sławińska, M. (2019). Przegląd metod oceny obciążenia zadaniowego w aspekcie doskonalenia układów operator - obiekt techniczny na przykładzie pilota. Journal of KONBiN, Vol. 49, sheet 3, 97-114.
  • 4. Casper, P., Kantowitz, B. (2009). Human Workload in Aviation.
  • 5. Davis, B. et al. (2014). Effective Teamwork and Communication Mitigate Task Saturation in Simulated Critical Care Air Transport Team Missions. Military Medicine, 179, 19-23.
  • 6. European Union Aviation Safety Agency - European Union Aviation Safety Agency - EASA (2022). Annual Safety Review.
  • 7. Gawron, V.J. (2008). Human Performance, Workload, and Situational Awareness Measures Handbook. Boca Raton: CRC Press.
  • 8. Hamann, A., Carstengerdes, N. (2020) Fatigue Instantaneous Self-Assessment (F-ISA): Development of a Short Mental Fatigue Rating. Retrieved from: https://elib.dlr.de/135577/, 26.08.2023.
  • 9. Hsu, W.-K. K, Shu, M.-H., Liu, Y.-C., Wang, T.-C. (2022). Risk Management of Safety for Flight Training in Air Forces. Aerospace, 9(10), 558.
  • 10. ISA Human Factors Methods (2023). Retrieved https://www.skybrary.aero/articles/instantaneous-self-assessment-isa, 3.07.2023. from:
  • 11. Jennings, S., Craig, G., Carignan, S., Ellis, K., Qinetiq, D.T. (2005). Evaluating control activity as a measure of workload in flight test. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 49(1), 64-67.
  • 12. Kang-Seok, L., Eun-Suk, S., Young, S. (2014). Impact of human factors for student pilots in approved flight training organizations in Korea. Aviation / Aeronautics / Aerospace International Research Conference, 45, 236-249.
  • 13. Maris, J.M., Haynes, M.A., Wing, D.J., Burke, K.A., Henderson, J., Woods, S.E. (2014). Traffic Aware Planner (TAP) Flight Evaluation. Retrieved from: https://ntrs.nasa.gov/api/ citations/20140011404/downloads/20140011404.pdf, 30.08.2023.
  • 14. Masi, G., Amprimo, G., Ferraris, C., Priano, L. (2023). Stress and Workload Assessment in Aviation-A Narrative Review. Sensors, 23(7), 3556.
  • 15. Nasa Task Load Index - NASA-TLX (2009). Retrieved https://humansystems.arc.nasa.gov/groups/tlx/downloads/TLX_pappen_manual.pdf, 26.06.2023. from:
  • 16. NASA TLX App Store. Retrieved from: https://itunes.apple.com/us/app/nasatlx/id1168110608?mt=8 (access: 26.06.2023)
  • 17. Radüntz, T., Fürstenau, N., Tews, A., Rabe, L., Meffert, B. (2019). The Effect of an Exceptional Event on the Subjectively Experienced Workload of Air Traffic Controllers. In: L. Longo, M. Leva (eds.), Human Mental Workload: Models and Applications.
  • 18. Romero, M.J., Robertson, M.F., Goetz, S.C. (2020). Fatigue in Collegiate Flight Training. The Collegiate Aviation Review International, vol. 38, No. 1.
  • 19. Rusnock, Ch.F., Geiger, Ch.D. (2017). Designing adaptive systems: selecting an invoking threshold to improve human performance. International Journal of Human Factors and Ergonomics, 4, 292-315.
  • 20. Sgobba, T. et al. (2017). Space Safety and Human Performance. Cambridge: ButterworthHeinemann
  • 21. Sun, H., Yang, F., Zhang, P., Zhao, Y. (2023). Flight Training Risk Identification and Assessment Based on the HHM-RFRM Model. Sustainability, 15, 1693.
  • 22. Szopa, T. (2015). Niezawodność i bezpieczeństwo. Warsaw: Publishing House of the Warsaw University of Technology.
  • 23. United States Department of Transportation. (2019). Workload Assessment, Retrieved from: https://railroads.dot.gov/human-factors/elearning-attention/workload-assessment. (access: 5.07.2023)
  • 24. Zhang, Y., Zheng, H., Duan, Y., Meng, L., Zhang, L. (2015). An integrated approach to subjective measuring commercial aviation pilot workload. IEEE 10th Conference on Industrial Electronics and Applications (ICIEA). Auckland, New Zealand, 1093-1098.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1eb0e9f8-7f72-4b75-a273-14ec9cd82e2f
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