Local airspace traffic prediction and flow control strategy recommendation system

This study focuses on improving the air traffic control and management of local airspace in China. We develop five modules to establish a decision-support system, which constitutes the analysis and strategy layer of a local airspace digital twin. This integrated solution utilizes multi-source multimodal data, ranging from flight status, weather, to real-time air traffic control strategies. Specifically, the first module reviews the operational performance of the airspace and assesses the maximum capacity of an airspace under particular weather scenarios. The second module forecasts the departure times of all incoming flights to inform potential congestion. The third module is the core module simulating the local airspace operation under given weather conditions and control strategies. In the fourth module, we compare the simulation results with the assessed capacities, and suggest adjustments to control strategies proposed by air traffic controllers. The fifth module applies mixed integer programming to obtain the optimal air traffic control strategies.