Human Factors Analysis of Air Traffic Safety Based on HFACS-BN Model

Tao Lyu,Ke Du,Wenbin Song

doi:10.3390/app9235049

Tao Lyu, Ke Du + Show 1 more

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https://doi.org/10.3390/app9235049

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Abstract

Air traffic control (ATC) performance is important to ensure flight safety and the sustainability of aviation growth. To better evaluate the performance of ATC, this paper introduces the HFACS-BN model (HFACS: Human factors analysis and classification system; BN: Bayesian network), which can be combined with the subjective information of relevant experts and the objective data of accident reports to obtain more accurate evaluation results. The human factors of ATC in this paper are derived from screening and analysis of 142 civil and general aviation accidents/incidents related to ATC human factors worldwide from 1980 to 2019, among which the most important 25 HFs are selected to construct the evaluation model. The authors designed and implemented a questionnaire survey based on the HFACS framework and collected valid data from 26 frontline air traffic controllers (ATCO) and experts related to ATC in 2019. Combining the responses with objective data, the noisy MAX model is used to calculate the conditional probability table. The results showed that, among the four levels of human factors, unsafe acts had the greatest influence on ATC Performance (79.4%), while preconditions for safe acts contributed the least (40.3%). The sensitivity analysis indicates the order of major human factors influencing the performance of ATC. Finally, this study contributes to the literature in terms of methodological development and expert empirical analysis, providing data support for human error management intervention of ATC in aviation safety.

Highlights

Safety is an important prerequisite for the sustainable and healthy development of the aviation industry [1]
Training contributes the most to the performance of air traffic controllers, which means that the professionals interviewed believe that the above human factors are most likely to exist in air traffic accidents related to air traffic controllers
HFACS-Bayesian network (BN) model provides an additional method for identifying the major human factors that may lead to aviation accidents

Summary

Introduction

Safety is an important prerequisite for the sustainable and healthy development of the aviation industry [1]. As a critical area of aviation safety, air traffic control (ATC) requires highly skilled operators to work together in a large and complex human–machine system [2]. Uncooperative interactions between controllers and system components hold potential for human errors, leading to safety breakdowns [5]. Human error is one of the contributors to more than 70% of aviation accidents [7]. This is demonstrated by a review of the Australian ATC system, which finds that coordination and communication errors contribute most to air traffic incidents [5]. In the UK Airprox incident report, human errors in ATC are related to perception, decision making, communication, and team resource management [8]

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