title: Predicting pilot error: testing a new methodology and a multi-methods and analysts approach.
abstract: The Human Error Template (HET) is a recently developed methodology for predicting design-induced pilot error. This article describes a validation study undertaken to compare the performance of HET against three contemporary Human Error Identification (HEI) approaches when used to predict pilot errors for an approach and landing task and also to compare analyst error predictions to an approach to enhancing error prediction sensitivity: the multiple analysts and methods approach, whereby multiple analyst predictions using a range of HEI techniques are pooled. The findings indicate that, of the four methodologies used in isolation, analysts using the HET methodology offered the most accurate error predictions, and also that the multiple analysts and methods approach was more successful overall in terms of error prediction sensitivity than the three other methods but not the HET approach. The results suggest that when predicting design-induced error, it is appropriate to use a toolkit of different HEI approaches and multiple analysts in order to heighten error prediction sensitivity.
authors.affiliation: University of Southampton, Transportation Research Group, School of Civil Engineering and the Environment Highfield, Southampton SO17 1BJ, UK.
authors.forename: Neville A
authors.initials: NA
authors.lastname: Stanton
authors.forename: Paul
authors.initials: P
authors.lastname: Salmon
authors.forename: Don
authors.initials: D
authors.lastname: Harris
authors.forename: Andrew
authors.initials: A
authors.lastname: Marshall
authors.forename: Jason
authors.initials: J
authors.lastname: Demagalski
authors.forename: Mark S
authors.initials: MS
authors.lastname: Young
authors.forename: Thomas
authors.initials: T
authors.lastname: Waldmann
authors.forename: Sidney
authors.initials: S
authors.lastname: Dekker
mesh_terms: D001359:Aviation / Q000592:standards*; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D017751:Safety Management / Q000379:methods*; D055815:Young Adult