Predicted growth in air traffic and the desire for more user preferred routes in the National Airspace System (NAS) will impose additional demand on air traffic control and management systems. This demand can be met by alternate airspace configurations, modified traffic patterns, and staff reassignment. There is a need to understand the effect of changing airspace configurations and traffic patterns on the workload of air traffic controllers. This complex relation is referred to as "Airspace Complexity". Research on dynamic density indicates that it is a good measure of airspace complexity. Dynamic density is a function of the number of aircraft and their changing geometries in a given airspace. In order to use dynamic density as a planning tool, it is necessary to project its behavior over the planning horizon. The objective of this work is to study how well dynamic density can be predicted into the future using the trajectory generation feature of the Center-TRACON Automation System (CTAS). This paper describes the application of trajectory prediction to computation of actual and predicted dynamic density using traffic data from Dallas/Fort Worth airspace. Results show that dynamic density can be predicted up to 20 minutes in advance and errors in predictions can be further
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