Modeling of Flight Time Prediction Uncertainty for Four-Dimensional Descent Trajectory Management

This study presents a model for flight-time prediction uncertainty on descent trajectories. Providing the magnitude of flight-time prediction uncertainty on descent trajectories is expected to enable efficient management of traffic flow towards congested airports without affecting safety. Flight-time prediction uncertainty inevitably increases as a flight progresses, owing to fluctuations of atmospheric conditions and aircraft control. In addition, atmospheric conditions and aircraft ground speed can vary significantly in descent trajectories. To develop a model for flight-time prediction uncertainty on descent trajectories, first a model of the increase in flight-time prediction uncertainty over short trajectory segments is derived theoretically. Its coefficients are determined through clustering and regression analysis of actual flight data and numerical weather forecast data. Then, a theoretical model of flight-time prediction uncertainty over descent trajectories is formulated to enable the calculation of flight-time uncertainty of descent trajectories using the short trajectory segment data. Through analysis of modeling accuracy of flight-time prediction uncertainty over a large number of actual descent trajectories, the proposed method is demonstrated to provide accurate flight-time prediction uncertainty of descent trajectories even under calm and severe conditions.