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

Lyu, Tao; Song, Wenbin; Ke, Du

doi:10.3390/app9235049

Cited by 25 publications

(13 citation statements)

References 33 publications

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“…The HFACS model defines the failures at four levels: unsafe behaviours, preconditions for unsafe behaviours, unsafety supervision and organizational management (Figure 2). This model is not only suitable for pilot risk management systems, but also has a good application in air traffic control man-made risk control (Lyu et al, 2019). The risk factors are mutually associated and influenced and jointly constitute a set of pilot unsafe behavioural risks.…”

Section: Methodsmentioning

confidence: 99%

Evolution Mechanism on the Unsafe Behavioural Risks of General Aviation Pilots

Guo

Chen²,

et al. 2021

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The unsafe behaviour prevention and control of general aviation pilots has become an emphasis in the general aviation safety management with the increasing number of general aviation enterprises, lengthening of flight time and frequent occurrence of public safety events caused by general aviation accidents. How to identify the factors influencing the unsafe behaviours of general aviation pilots and clarify the inter factor evolution mechanism is hot issue in the general aviation. To accurately identify the key factors influencing the unsafe behaviours of general aviation pilots and define the interaction mechanism between factors, using the unsafe behaviours of pilots in 200 global general aviation accidents during 2015-2019 and the association rule method, the bottom-layer factors of the Human Factors Analysis and Classification System (HFACS) model were analysed. Furthermore, the influence degree, influenced degree, centrality and causality of the influencing factors in the HFACS model were calculated, and the risk transfer path at different layers was determined on the basis of the integrated decision-making trial and evaluation laboratory (DEMATEL) and fuzzy theory. Results show that the poor individual ready state is strongly associated with skill error, decision-making error and habitual violation. Moreover, 11 factors, such as poor physical environment, physical/intelligence limitation and poor technical environment, constitute the factors in the cause group for pilot unsafe behaviours. 7 factors, such as insufficient supervision, improper operation plan and failure to discover and correct problems, are the factors in the result group. Illegal behaviour, failure to discover and correct problems and decision-making error of pilots, which are of high centrality, are key factors influencing the unsafe behaviours of general aviation pilots. The conclusions obtained from this study compensate the deficiencies for the linear statistical model of risk factors and provide a novel method for regulating and controlling the unsafe behaviours of general aviation pilots.

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Section: Methodsmentioning

confidence: 99%

Evolution Mechanism on the Unsafe Behavioural Risks of General Aviation Pilots

Guo

Chen²,

et al. 2021

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“…Each level corresponds to one layer of the Swiss Cheese Model. The advantage of HFACS is that it considers the organizational factors in the cause of accidents, which makes it an effective tool for the analysis of human factors in aviation accidents [ 34 ], and has been widely used in maritime [ 35 ], HCs transportation [ 36 ], mining [ 37 ], and other fields. However, the two approaches still consider that accidents are a result of a series of mutual causal events, although they do consider the complexity of the accident process and could reveal the relationship between potential cause and direct cause in the accidents.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China

Zhang

et al. 2021

IJERPH

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Safety of the hazardous chemicals road transportation system (HCRTS) is an important, complex, social, and environmental sensitive problem. The complexity, dynamics, and multi-link features of HCRTS have made it necessary to think beyond traditional risk analysis methods. Based on the relevant literature, Functional Resonance Analysis Method (FRAM) is a relatively new systemic method for modeling and analyzing complex socio-technical systems. In this study, a methodology that integrates FRAM, fuzzy sets, and risk matrix is presented to quantitatively assess the risks factors representing failure function links in HCRTS. As the strength of function links can be illustrated by the RI (risk index) of risk factors identified in failure function links, 32 risk factors representing 12 failure function links were first identified by accident causes analysis and the framework of FRAM. Fuzzy sets were then utilized to calculate the weight of the likelihood and consequence of the risk factors. Finally, according to the assessment results of the identified risk factors by a two-dimensional risk matrix, the weaker function links in the whole HCRTS chain were identified. HCs road companies, regulatory authorities, relevant practitioners, and other stakeholders should pay more attention to these links.

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“…At present, there are many studies have used BN to identify causation factors of accidents or predict the safety status under certain conditions. For example, Xia et al [34] established BN model to predict the safety performance in the field of construction projects, while Tao et al [37] used BN-HFACs model to analyze the human factors of air traffic accidents. Although these studies applied in different scenarios or purposes, it can be concluded that BN could be used in this paper to analyze the causes of HCAs.…”

Section: Bn-hfacsmentioning

confidence: 99%

Cause Analysis of Unsafe Behaviors in Hazardous Chemical Accidents: Combined with HFACs and Bayesian Network

Liu

Liu³

2019

IJERPH

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Hazardous chemical accidents (HCAs) seriously endanger public life, property, and health. Human and organizational factors are important causes of many kinds of accidents. In order to systematically explore the influencing factors of unsafe behaviors in HCAs in China, the method of human factors analysis and classification system based on the Bayesian network (BN-HFACs) was introduced. According to the 39 investigation reports of HCAs in China, the origin Bayesian network (BN) was obtained and the failure sensitivity of every node in BN was calculated. The results have shown that hazardous material environment (1.63) and mechanical equipment (0.49) in the level of preconditions of unsafe behavior have the same direction failure effect with operation error, while there is no factor has the same direction failure effect with operation violate. Some factors in organization influence and unsafe supervision, such as organization climate (0.34), operation guidance (0.37), planned operation (0.22), and legal supervision (0.19), are also important reasons for operational errors, while resource management (0.12), hidden investigation (0.18) and legal supervision (0.13) have an impact on operation violates. Moreover, there are still close relationships between other hierarchical elements, such as the operation guidance effect on the hazardous material environment (6.60), and the organizational climate has the most obvious impact on other factors at the level of organizational factors. Based on the above research conclusions, suggestions for individual, enterprise, and government were put forward, respectively, and the limitations of this study were also clarified.

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

Cited by 25 publications

References 33 publications

Evolution Mechanism on the Unsafe Behavioural Risks of General Aviation Pilots

Evolution Mechanism on the Unsafe Behavioural Risks of General Aviation Pilots

Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China

Cause Analysis of Unsafe Behaviors in Hazardous Chemical Accidents: Combined with HFACs and Bayesian Network

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