Analysis and Forecast of Global Civil Aviation Accidents for the Period 1942-2016

Abstract EN

With the increase of global civil aviation transportation, more and more researchers pay attention to the analysis of civil aviation accidents.

Time series analysis can obtain the variation law in a large amount of data, and there is no research result of aviation accident time series yet.

Based on the Mann-Kendall trend analysis and mutation analysis methods, this paper studied the change trend of accidents and casualties in different flight stages of civil aviation and built ARIMA (Autoregressive Integrated Moving Average model) time series analysis model to predict the number of civil aviation accidents and casualties by the long-term data in the world.

(1) The number of civil aviation accidents fluctuates generally in the world; from 1942 to 2016, there were two fluctuation periods of civil aviation accidents.

(2) The number of global civil aviation casualties from 1942 to 2016 showed a parabola trend of increasing first and then decreasing.

The highest number of casualties appeared in 1972, which was 2373; on the different flight stages, the number of accidents was different.

In the air route and approach phase, the number of accidents was the most, and the number of casualties was more than other flight phases, accounting for about 50% of the whole flight phase.

(3) In addition to the land phase, the number of accidents showed a significant decrease in other flight phases; while the air route and total number of casualties decreased significantly, the number of casualties at other flight phases did not decrease significantly.

There were no sudden changes in the number of global civil aviation accidents and approach casualties.

(4) The sudden change point of the global civil aviation casualties was 2013, the sudden change point of the air route stage accidents was 1980, the sudden change point of approach stage accidents was 2012, and the sudden change point of air route stage casualties was 2006.

According to the ARIMA (1,0,1) model, the numbers of global civil aviation accidents and casualties were predicted to 2025.

Through time series research, we have explored the variation law in the historical data of long-term aviation accidents and predicted the possible changes of future aviation accidents, providing data reference for aviation safety research.