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An empirically benchmarked human reliability analysis of general aviation

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  • Burns, Kevin
  • Bonaceto, Craig

Abstract

A Human Reliability Analysis of general aviation is empirically benchmarked, using Probabilistic Risk Assessment methods and historical accident rate data. The analysis posits three types of pilot actions, namely Knowledge-based, Rule-based, and Skill-based, each with a nominal human error probability treated as an unknown parameter. Various performance shaping factors are treated as known multipliers to these probabilities in quantifying pilot-related accident sequence equations. The equations are aligned with accident frequencies reported in a general aviation safety database, which includes nearly one thousand accidents in over twenty million flights annually. These equations are then solved for values of the three variables, thereby establishing an empirical basis for the assumed types of actions and associated performance shaping factors. The resulting model, benchmarked against retrospective data, is also used in prospective fashion to quantify the ergonomic impacts and safety benefits of a prototype system that provides pilots with cognitive assistance in general aviation.

Suggested Citation

  • Burns, Kevin & Bonaceto, Craig, 2020. "An empirically benchmarked human reliability analysis of general aviation," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:reensy:v:194:y:2020:i:c:s0951832017310219
    DOI: 10.1016/j.ress.2018.07.028
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    References listed on IDEAS

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    1. Boring, Ronald L. & Hendrickson, Stacey M.L. & Forester, John A. & Tran, Tuan Q. & Lois, Erasmia, 2010. "Issues in benchmarking human reliability analysis methods: A literature review," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 591-605.
    2. Laumann, Karin & Rasmussen, Martin, 2016. "Suggested improvements to the definitions of Standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) performance shaping factors, their levels and multipliers and the nominal tasks," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 287-300.
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    1. Zhao, Yunfei & Smidts, Carol, 2021. "CMS-BN: A cognitive modeling and simulation environment for human performance assessment, part 2 — Application," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Hu, Lunhu & Pan, Xing & Ding, Song & Zuo, Dujun & Kang, Rui, 2022. "A quantitative input for evaluating human error of visual Neglection: Prediction of Operator's detection time spent on perceiving critical visual signal," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

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