Using Existing HEI Techniques to Predict Pilot Error: A Comparison of SHERPA, HAZOP, and HEIST

Paul Salmon, Neville A. Stanton, Mark S. Young, Don Harris, Jason Demagalski, Andrew Marshall, Thomas Waldon and Sidney Dekker

At the moment, there appears to be no human error identification (HEI) techniques developed specifically for use in aviation. Similarly, there appears to be very little research concerning the prediction of pilot error in the cockpit. This paper investigates the potential use of existing HEI methods for predicting pilot error and describes a comparative study of three existing HEI techniques, SHERPA, HAZOP and HEIST when used to predict potential pilot error on an aviation landing task using the “autoland” system. The study aims to demonstrate that existing HEI methods developed for use in highly complex systems, such as nuclear power plants and chemical processing plants, can be used effectively in an aviation context.

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