Citation

Burns K, Bonaceto C. Reliab. Eng. Syst. Safety 2020; 194: e106227.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.ress.2018.07.028

PMID

unavailable

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.

Language: en

Keywords

Accident rate data; General aviation; Human error probability; Human reliability analysis; Performance shaping factors; Probabilistic risk assessment