A Methodology and Results for Comparative Assessment of the Prediction Performance of the Collaborative Routing Coordination Tools (CRCT)

The Collaborative Routing Coordination Tools (CRCT) is the prototype of a set of tools to help the Federal Aviation Administration (FAA) to detect traffic flow problems in advance, to generate problem resolutions, and to evaluate the resolution strategies. CRCT does this by modeling four-dimensional aircraft trajectories and using them to predict demand for sector usage. A methodology was developed and used to compare the prediction performance of CRCT under various software and data configurations. The methodology can be and has been used for other tools (e.g., the Enhanced Traffic Management System (ETMS)) that predict sector demand. Several performance metrics were defined and tools were developed to calculate the metrics from prediction data and actual track data. The metrics assess how closely predictions match the sector loads that actually occur. This paper presents the methodology used to assess CRCT's prediction performance and the results of various comparative performance analyses. The analyses are based on CRCT runs against recordings of actual air traffic data on both good and bad weather days. Analysis results are compared for the two weather days and for three Air Route Traffic Control Centers (ARTCCs).