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Paper 121 -- Calibrating Aggregate Models of Flight Delays and Cancellation Probabilities at Individual Airports

This paper describes methods to calibrate aggregate models of internal delays and cancellations at a single airport. Internal delays are those specifically related to queuing effects at the arrival airport; i.e., they are induced because of a local imbalance between demand and capacity. Together with cancellations, these delays reflect important measures of system performance that are directly affected by carrier scheduling policies, as well as airport and FAA decisions about operating policies that affect capacity. We are concerned with models that might be able to produce outputs that are specific to carriers, but in any event cannot be calibrated with proprietary information, because the issues concern multiple carriers or are approached from the public perspective. Such models are appropriate, for example, when considering operational impacts of demand or capacity changes resulting from changes in infrastructure, resource allocation, or landing fees. Thus, the ground truth calibration data must come from publicly available aggregate data bases. The models themselves are unaware of some of the true drivers for cancellations and delays, and rely more on empirical correlations between these performance measures and public supply and demand information. The paper describes our experiences and recommendations about calibrating such models, including data filtering methods. Specific examples from our own efforts at model development are included, but the calibration methods described herein should be applicable to alternative model forms as well.
Theme: Active ATM Performance Management
Posted by: David Lovell / Other authors: Andrew Churchill, Amedeo Odoni, Avijit Mukherjee, Michael Ball
Note: Unset Received On Jan 26, 2007

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