Risk Topics Discovery and Trend Analysis in Air Traffic Control Operations—Air Traffic Control Incident Reports from 2000 to 2022

Wenquan Liu, Honghai Zhang (), Zongbei Shi, Yufei Wang, Jing Chang and Jinpeng Zhang
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Wenquan Liu: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Honghai Zhang: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Zongbei Shi: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Yufei Wang: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Jing Chang: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Jinpeng Zhang: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Sustainability, 2023, vol. 15, issue 15, 1-17

Abstract: The safety of air traffic control (ATC) operations is an important cornerstone for the sustainable development of the civil aviation industry. In order to clarify the risk factors in the control operation process and to achieve digital representation of the safety risks of civil aviation control operations, starting from the ATC incident reports, we fully mine the safety risk information and unspoken rules of ATC operations. A risk perception model for air traffic control operations safety based on the Latent Dirichlet Allocation (LDA) topic model and the Semantic Network Based on BERT (BSN) model is suggested. First, 17 risk topics and keywords were found in the incident reports collected using the LDA topic model. These topics included those pertaining to the stage of aircraft operation, human factors in control operation, and the sector or airspace operation status and structure. The findings indicate that while most risk subjects have not changed significantly, they do show an upward tendency. Human factors and operational rules and procedures account for the highest share of all key causes, and they also have a significant impact on how risk topics evolve over time. Finally, the BSN model in the air traffic control field was built based on the keywords of each risk issue in order to highlight any potential correlations between distinct risk topics. The results show that some risk topics have interrelated risk characteristics, and there are regularities of mutual evolution between these risk topics. The relevant research results can better mine air traffic control unsafe information and lay a foundation for accurately perceiving air traffic control operations risks.

Keywords: air traffic control (ATC); risk management; incident report; text mining; topic model; Latent Dirichlet Allocation (LDA); BERT; semantic network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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