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Paper 7 -- Measurement And Prediction Of Dynamic Density

This paper describes results of a multi-year, multi-organizational research initiative related to the measurement and prediction of sector level complexity called Dynamic Density (DD). The researchers first identified a number of candidate DD measures. They then identified eighteen 30-minute traffic samples from each of four selected en route Air Route Traffic Control Centers (ARTCCs). At each ARTCC, they collected complexity ratings at two-minute intervals for each traffic sample from approximately 70 air traffic controllers and supervisors. Using the traffic and sector data, various DD variables were computed. Using a linear regression method, the relationships between different DD variables and complexity ratings were determined. A unified DD metric composed of variables from several organizations performed the best. The results indicated that DD represents instantaneous sector complexity better than aircraft count, which is the currently used method. The results also indicated that the prediction of complexity using DD is somewhat better than the prediction using aircraft count most likely due to the inherent inaccuracy of predicting aircraft count.
Theme: Metrics and Performance Management
Posted by: Parimal Kopardekar / Other authors: Sherri Magyarits
Note: Unset Received On Dec 20, 2005

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