Robust airspace design methods for uncertain traffic and weather

We present a robust optimization framework for performing Dynamic Airspace Configuration (DAC) integrated with Traffic Flow Management (TFM) under weather uncertainties. We extend the existing cell-based Mixed Integer Programming (MIP) model along with the GeoSect sectorization method to incorporate probabilistic weather predictions in airspace sectorization. An ensemble generation method is devised to take a probabilistic weather forecast and generate weather ensembles. The weather ensembles are then fed into a TFM agent developed to compute weather avoidance 4D trajectories (4DT) and to create traffic ensembles. Robust sectorization algorithms use traffic and weather ensembles to produce robust sector boundaries that are feasible and close to optimal for each of the traffic ensembles. Several experiments are presented for testing the degree of robustness of generated sectors across different traffic ensembles.