Abstract
One of the pressing problems in the field of air traffic control — the choice of routes for the redistribution of aircraft flows is considered. The air traffic controller determine decision on the choice of routes for the redistribution of air traffic flows directly in flight based on personal experience, level of professionalism and availability of variations. It is proposed to improve the airspace planning system using statistical data, accumulated experience, feedback from airspace users together with machine learning technology and a neural network. The developed route selection system is tested using the example of choosing the most economically preferable route for an aircraft. Keywords air traffic control, redistribution of air traffic flows, failure situation, airspace use scenario, dispatcher workload, economic efficiency, machine learning
Published Version
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