A human factors accident analysis framework for UAV loss of control in flight

Sixty Uncrewed Aerial Vehicle accident reports were analysed to identify causal and contributory factors leading to loss of control in flight – the most prominent category of UAV accident (36%). Design and manufacturing errors were dominant causal factors (22 events, 34%) and contributory factors (18 events, 22%). Recovery was not attempted in the majority of events (35 events, 55%). The relationship between operator age, total hours of experience, experience on type and recovery attempts were analysed. The number of accidents decreased as total hours of experience increased as well as attempted recovery. Using this data, existing accident analysis frameworks HFACS, AcciMap and Accident Route Matrix were applied to a sample of accidents and suitability compared. An adapted version of the Accident Route Matrix – Uncrewed Aerial Vehicle is proposed to assist current and future operators to understand causal and contributory factors to mitigate future loss of control in flight accidents and improve the likelihood of recovery. Using the results of the statistical analysis and the data gathered, a new definition for LOC-I for UAVs was defined by considering the different operating environment of UAVs.

Publication Details

Journal
Research Portal (King's College London)
Published
2025-02-17
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

A human factors accident analysis framework for UAV loss of control in flight

Research Portal (King's College London)
Human-Automation Interaction and Safety
article

A human factors accident analysis framework for UAV loss of control in flight

article en

Abstract

Sixty Uncrewed Aerial Vehicle accident reports were analysed to identify causal and contributory factors leading to loss of control in flight – the most prominent category of UAV accident (36%). Design and manufacturing errors were dominant causal factors (22 events, 34%) and contributory factors (18 events, 22%). Recovery was not attempted in the majority of events (35 events, 55%). The relationship between operator age, total hours of experience, experience on type and recovery attempts were analysed. The number of accidents decreased as total hours of experience increased as well as attempted recovery. Using this data, existing accident analysis frameworks HFACS, AcciMap and Accident Route Matrix were applied to a sample of accidents and suitability compared. An adapted version of the Accident Route Matrix – Uncrewed Aerial Vehicle is proposed to assist current and future operators to understand causal and contributory factors to mitigate future loss of control in flight accidents and improve the likelihood of recovery. Using the results of the statistical analysis and the data gathered, a new definition for LOC-I for UAVs was defined by considering the different operating environment of UAVs.

Research Portal (King's College London)
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A human factors accident analysis framework for UAV loss of control in flight · Research Portal (King's College London) (2025) | TGRS Research Map | TGRS