Abstract:

In order to achieve a quantitative evaluation of individual pilot's exceedance risk, a refined evaluation model for pilot's individual exceedance risk was established based on QAR data and the flight operations quality assurance(FOQA) monitoring items. Firstly, according to accident statistics, International Civil Aviation Organization (ICAO) and the core risks divided by the FOQA station, the FOQA monitoring items associated with the three types of core risks were selected as the evaluation indexes, and the risk value for each core risk of the individual pilots was calculated. In the next step, the weight of each core risk value was calculated by entropy weighted TOPSIS. Then, the refined evaluation model for the pilot's individual exceedance risk was established. Finally, the model was applied to the quantitative evaluation of actual flight risk. By collecting 9 317 pieces of multi-source fusion data from the FOQA station of Civil Aviation Administration of China (CAAC), the individual exceedance risk of the pilots were quantified, the ranking of individual pilots' exceedance risk was obtained, and the pilot's individual exceedance risk levels were also divided with the use of K-means clustering algorithm. The results show that the model can quantify and rank 1 693 individual pilots' exceedance risk, and divide the pilot's exceedance risk into three types, including high risk, medium risk and low risk.

Key words: quick access recorder (QAR) data, individual exceedance risk, refined evaluation, flight operations quality assurance (FOQA), entropy-weighted technique for order preference by similarity to an ideal solution(TOPSIS), K-means clustering