Study on Regional Division of Air Traffic Management in Mainland China in the Future

Abstract

With the problems of poor coordination and frequent flight delays among major air traffic control regions in mainland China becoming increasingly prominent, a series of air traffic control reform measures are imperative. In order to meet the development need of the transition from a large civil aviation country to power one in the future, it is necessary to divide the air traffic management regions reasonably in advance. Therefore, based on the flights between the airports from 2011 to 2017, this paper combines the grey prediction algorithm with the gravity model and considers the impact of high-speed rail on the flights of civil aviation, then constructs the grey gravity prediction model. According to the forecast result of the future airport flow by the grey gravity prediction model, the flight plans of each airport are generated by using the equal proportion enlargement method. On the basis of the flight plans of each airport, the flight situation in mainland China at a certain time is simulated. According to the simulated aircraft longitude and latitude data, the optimal clustering results are obtained by using the fuzzy C-means clustering algorithm and clustering validity evaluation index. Finally, the clustering results are processed by clustering boundary recognition algorithm, the future air traffic management regional division results in mainland China are obtained. The experimental results show that the prediction accuracy of the grey gravity prediction model considering the influence of high-speed rail is better than the traditional grey prediction algorithm, and the original seven major air traffic control zones in mainland China are re-divided into three major air traffic control zones: North China, South Central China and Northwest China, which can provide reference for future air traffic control reform and development.