Comparison of the Performances of Two Aggregate Air Traffic Models

Inspired by an existing linear dynamic system air traffic model, a discrete-time Link Transmission Model is developed for air traffic flow prediction and optimization in this paper. Compared with a Large-capacity Cell Transmission Model, this model reduces the number of state variables by approximately an order of 10, which decreases the computing time in prediction and optimization of air traffic flow. Comparison and analysis regarding the prediction accuracy and computational efficiency of the new model are performed based on two benchmark scenarios, one including a simple case with two cross flight paths, the other including the entire National Airspace System. Numerical results of this study show that the Link Transmission Model achieves a same level of accuracy as Large-capacity Cell Transmission Model in air traffic prediction , and the computational efficiency is significantly improved with an equally optimal solution in air traffic optimization.