Probabilistic Methods for Airspace Sector Flow and Congestion Prediction

In order to improve the accuracy of sector flow forecasting and diminish false congestion alerts, probabilistic models for sector entry time, sector transit time and sector exit time were established through analysis of the uncertain factors influencing air traffic operations. Then, a probabilistic method for calculating the sector occupancy by an aircraft was built using the cumulative distribution functions of sector entry time and exit time. On this basis, a probabilistic method for sector congestion prediction based on Monte Carlo simulation was proposed. The simulation results show that, compared with the deterministic method, the proposed probabilistic method could decrease the ratio of congestion time intervals from 42% to 33%.