A data-driven model of human factors contributing to loss of control in-flight and on the ground in general aviation

Esmaeil Zarei

doi:10.1016/j.ress.2025.112124

A data-driven model of human factors contributing to loss of control in-flight and on the ground in general aviation

2025-12-16

0

PRE

AI

E

Esmaeil Zarei

B

Brian J. Roggow *

K

Kamran Gholamizadeh

K

Kelly Hansen

C

Caleb Langel

DOI：10.1016/j.ress.2025.112124

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Abstract

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• Novel ML–DBN framework for retrospective and predictive human error analysis. • Empirical CPT construction from co-occurrence data reduces subjectivity. • Bayesian forecasting with Monte Carlo enables monthly risk trajectories. • Upstream precursors identified as most effective intervention targets. • Modular Python framework scalable across diverse aviation contexts.

A data-driven model of human factors contributing to loss of control in-flight and on the ground in general aviation

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