Development of a Flight Time Uncertainty Model for Four-Dimensional Trajectory Management

Abstract

The paper presents a model of the flight time uncertainty based on flight conditions and weather forecasts for aircraft flying at arbitrary distances for use in four-dimensional (4-D) trajectory management. Fluctuations in meteorological conditions inevitably result in an increased flight time uncertainty despite constant monitoring and control of the aircraft’s Mach number, flight altitude, and direction. A series of actual flight data acquired from secondary surveillance radar mode S and numerical weather forecast data was analyzed to provide a large number of samples for flight time errors. A mathematical model of the flight time uncertainty as a function of ground speed, Mach number, flight distance, and wind and temperature forecasts was modeled based on the law of propagation of uncertainty considering the correlation between temperature and wind fluctuations. Cluster and linear regression analyses were used to determine the function coefficients. The evaluation results show that the proposed model can accurately estimate the flight time uncertainty for an aircraft flying at arbitrary distances, even under calm or severe weather conditions. The proposed model has the potential to simultaneously improve the safety and efficiency of 4-D trajectory management.