Risk prediction and early warning of pilots’ unsafe behaviors using association rule mining and system dynamics

Qin Xiao, Fan Luo, Yapeng Li and Dan Pan

Journal of Air Transport Management, 2023, vol. 110, issue C

Abstract: Risk prediction of pilots' unsafe behaviors is of great significance for preventing unsafe aviation incidents. However, there is a lack of effective and precise approach of dealing with this problem. This study proposes a hybrid approach of combining association rule mining (ARM) method and system dynamics (SD) model to predict and warn pilots' unsafe behaviors. Firstly, the risk factors are identified and classified according to the historical incident data by the human factor analysis and classification system. Then, the association rules between risk factors and unsafe behaviors are obtained by ARM. Finally, the SD is adopted to construct the risk prediction and early warning model for pilots' unsafe behaviors, and the applicability and effectiveness of the model are verified by the actual data from 2016 to 2020. The results of ARM show that there are 48 risk factors affecting pilots' unsafe behaviors, and 142 key association rules are formed between these risk factors and unsafe behaviors; environmental influences, pilots' adverse states, and organizational influences are all strongly related to pilots' unsafe behaviors, and the impact of environmental influences on unsafe behaviors mainly rely on the interaction with other factors. The results of SD demonstrate that although both of the cognitive error risk and the decision error risk show an increasing trend, the former increases slowly and keeps at the level of no alarm while the latter is growing faster and its risk may increase from no alarm to critical alarm; the operation error risk and the violation risk both show a downward trend, and finally remain at the no alarm level; the risk of pilots' unsafe behaviors has a stable fluctuation trend, and the risk values of most time are in the threshold ranges of major warning and critical warning. This work provides theoretical guidance for the decision-makers to develop measures to reduce incidents caused by pilots’ unsafe behaviors.

Keywords: Pilots' unsafe behaviors; Risk prediction; Early warning; Association rule mining; System dynamics (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:110:y:2023:i:c:s0969699723000650

DOI: 10.1016/j.jairtraman.2023.102422

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