The Analysis of Controlled Flight Into Terrain Incidents From Flight Crew Perspective Using Named Entity Recognition and Bayesian Networks

Abstract

Controlled flight into terrain (CFIT) can result in significant aircraft damage and human casualties. Analyzing incident factors and their evolutionary relationships in aviation safety reports helps explore the inherent mechanisms of CFIT, thereby potentially reducing their occurrence. This study proposes a methodology combining named entity recognition (NER) and Bayesian network (BN) to address the challenges of efficiently extracting incident factors from textual reports from the crew’s perspective and analyzing the overall evolution process of CFIT incidents to better prevent accidents. First, this study collected 354 CFIT incident reports in the Aviation Safety Reporting System (ASRS) for the period November 2021 to August 2023. Second, important concepts from Threat and Error Management (TEM) were referenced to determine principles for extracting factor types and their evolutionary relationships. Third, NER was applied using the BERT–BiLSTM–MHA–CRF model to extract incident factors, followed by model comparison. Experimental results demonstrated good performance with precision, recall, and F1 score of 0.97, 0.90, and 0.90, respectively. Last, BN was then employed to analyze the CFIT evolution process. Results indicate that if factors such as Terrain (0.04) and Unfamiliarity/Inexperience (0.036) are present, CFIT risk will increase. Conversely, if protective factors such as Perfect Weather/Great Visibility (0.397) and Perform the Escape Maneuver (0.341) are present, CFIT risk will decrease. The analysis reveals that Airline Operational Pressure, Fatigue (57%), Lack of Situational Awareness (21%), Automation Errors (45%), Aircraft Handling Deviations (34%), Aviation System–Based Countermeasures (72%), Perform the Escape Maneuver (75%), and Make a Stabilized Approach (89%) form the highest probability evolution pathway for CFIT incidents. This study concludes that reducing these identified risk factors and increasing protective factors can contribute to reducing CFIT accidents.