Abstract:

There are still no effective airspace congestion management strategies and methodologies to slove seriously increased airspace congestion. An airspace congestion prediction model and an airspace congestion resolution model were established. The airspace congestion prediction model was used to forecast the time intervals in which the congestion occurred, and the airspace congestion resolution model was used to control the air traffic flow in the airspace with high risk congestion during predicted time intervals. The airspace congestion risk was reduced, and also  some factors such as delay cost, delay equity of different airspace users and the influence to the air traffic flow were considered. Based on  real flight data,  simulation results showed that the two models could effectively predict the time of airspace congestion in the future, rapidly find out  suitable strategies, and balance performance risk control and cost control, which provided an innovative new way for dynamic air traffic flow management.

Key words: air traffic, air traffic flow management, risk prediction, airspace congestion management