An Aggregate Air Traffic Forecasting Model subject to Stochastic Inputs

Abstract

This paper introduces an aggregate air traffic model that calculates the number of aircraft in each Air Route Traffic Center in the United States at any time iteration. The algorithm has the feature of being able to compute the shortest path of an aircraft using future previsions. Weather perturbations and available resources are two main types of input that have a stochastic nature due to their uncertainties. Too often they result in last minute delays or flight cancellations. Thus when predictions are available, their integrations in the path computation modify the aircraft trajectories accordingly, generating robust flight plans. More importantly, this algorithm handles different aircraft types which fly at different cruising speeds, making the scenarios being tested more realistic. Three simple scenarios were tested to validate this aggregate model. A large scale example using historical traffic data of a typical day in the National Airspace System is also presented. The results in comparison with uncontrolled simulations performed in the Future Automation Concepts Evaluation tool show that the model constitutes a potential Traffic Flow Management strategy. Nomenclature

Original document

The different versions of the original document can be found in:

• http://pdfs.semanticscholar.org/6c1f/3abb0034676a0e9202373f86270dd5616e05.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2013-5032,

http://dx.doi.org/10.2514/6.2013-5032

• https://arc.aiaa.org/doi/10.2514/6.2013-5032,

http://web.ics.purdue.edu/~dsun/pubs/gnc13b.pdf,

https://academic.microsoft.com/#/detail/2129919448