UC Irvine

The volume of air traffic in the National Air Space has been growing at a very fast pace during recent years, and increasing demand for air travel in coming years is predicted. Strategic Planning is a necessary tool to guarantee a safe and efficient increase of Air Traffic. An Aggregate Model for Strategic Planning of Air Traffic Management is the framework of this project.

Aggregate models require the creation of a network that is representative of the expected flow and which will serve as a platform to solve flow optimization problems. We have integrated an automatic method for route clustering - Smax method - to generate the required network. Automatic clustering is necessary in order to efficiently cluster many individual scenarios.

Some available alternatives to determine the number of clusters are tested. The studied alternatives provide success rates that oscillates between 49% and 68%. In addition to the relatively low success rates, these methods require one user-input parameter, and they are highly sensitive to it.

A different method, based on the Silhouette Score and the Dip Test measures, is developed. The Smax method requires no user-input parameters, and it consistently provides rates of success that approximately oscillate between the 72% and the 81%.

The presented clustering approach noticeably improves the rate of correct clustering cases for the specific scenario of route clustering.