Describing air traffic flows using stochastic programming
Résumé
The objectives of Air Traffic Management (ATM) system is to ensure safe and efficient operation of an individual flight as well as to maximize the overall capacity and minimize the adverse environmental impacts of the air transportation system. To achieve these objectives, airspace capacity, which drives capacity and traffic flow management policies, should be more properly estimated according to the detailed traffic configuration. There have been some efforts to describe the complexity of a traffic situation based on the idea of modeling airspace onto a dynamical system. This paper extends the previous research efforts by accounting for uncertainties on aircraft's positions and velocities. The proposed method is illustrated with examples.
Mots clés
airspace of interest
position of aircraft at ti
velocity of aircraft at ti
nonlinear vector field model for airspace D
linear vector field model for airspace D
reference point in time for linearization
reference point in space for linearization
position of aircraft at ti as a random variable
velocity of aircraft at ti as a random variable
Frobenius norm
window function
variable number