A Hybrid Model Integrating HFACS and BN for Analyzing Human Factors in CFIT Accidents

Abstract

Controlled flight into terrain (CFIT) is considered a typical accident category of “low-probability-high consequence”. Human factors play an important role in CFIT accidents in such a complex and high-risk system. This study aims to explore the causal relationship and inherent correlation of CFIT accidents by the Human Factors Analysis and Classification System (HFACS) and Bayesian network (BN). A total of 74 global CFIT accident investigation reports from 2001 to 2020 were collected, and the main contributing factors were classified and analyzed based on the Human Factors Analysis and Classification System. Then, the model was transformed into a Bayesian network topology structure. To ensure accuracy, the prior probability of each root node was computed by the fuzzy number theory. Afterward, using the bidirectional reasoning ability of the Bayesian network under uncertainty, this study performed a systematic quantitative analysis of the controlled flight into terrain accidents, including causal reasoning analysis, diagnostic analysis, sensitivity analysis, most probable explanation, and scenario analysis. The results demonstrate that the precondition for unsafe acts (30.5%) has the greatest impact on the controlled flight into terrain accidents among the four levels of contributing factors. Inadequate supervision, intentional noncompliance with SOPs/cross-check, GPWS not installed or failure, adverse meteorological environment, and ground-based navigation aid malfunction or not being available are recognized as the top significant contributing factors. The contributing factors of the high sensitivity and most likely failure are identified, and the coupling effect between the different contributing factors is verified. This study can provide guidance for CFIT accident analysis and prevention.

Risk Analysis of Airplane Upsets in Flight: An Integrated System Framework and Analysis Methodology

“…The civil aviation safety system is complex with risk factors involving employees, all kinds of equipment, the working environment, and the organization [12,13]. The civil aviation industry has reached a consensus that civil aviation accidents are often not caused by a single factor but by defects at various levels of the system in most cases [14,15]. Similarly, the risk factors leading to airplane upsets are complex and changeable.…”

“…Airplane upsets are the result of the nonlinear and dynamic evolution of risk under the interaction of various risk factors [14]. To ensure the reliability and accuracy of the study, we mainly adopt two methods to extract the main risk factors that lead to airplane upsets: (1) by sorting and analyzing the research literature in Section 2, the risk factors were preliminarily extracted; (2) retrospective analysis and classification analysis were carried out on the 72 investigation reports of typical accidents or incidents in 2000-2020 (40 commercial transport aviation investigation reports and 32 general aviation investigation reports) caused by airplane upsets.…”

“…It refers to blind confidence in one's flight ability or experience, proof of flight ability through risky operation, or self-assumption that everything is normal and insufficient attention to a safety risk or even intentional violation [14].…”