| Predicting Congestion in
the Northeast U.S.: A Search for Indicators
April 2000
Emily Beaton, The MITRE Corporation
John F. Brennan, The MITRE Corporation
James S. DeArmon, The MITRE Corporation
J. Jeffrey Formosa, The MITRE Corporation
Kerry M. Levin, The MITRE Corporation
Shane Miller, The MITRE Corporation
Craig Wanke, The MITRE Corporation
ABSTRACT
The northeast U.S. is arguably the most congested airspace in the world.
Four major New York airports have very high total operations counts
and are concentrated geographically. Improvements are needed for flow
managers' decision support systems, to support proactive intervention
leading to smoother arrival flows. A CAASD team addressed this issue
by investigating predictive "indicators", i.e., quantifications
that foretell a future situation with respect to the balance of air
traffic demand and capacity at airspace resources. Most flights in the
northeast last less than 70 minutes, so predictions of airspace congestion
at least one hour ahead would be most useful, since flow control could
therefore extend to pre-departure. Predictions are needed especially
during visual meteorological conditions, when congestion is not necessarily
an expected outcome. Our approach was to examine historical data, in
search of identifiable air traffic management problem situations. These
situations were then played-back using an integrated real-time model,
combining two previously built CAASD systems (the Self-Managed Arrival
Resequencing Tool [SMART] and the Collaborative Routing Coordination
Tool [CRCT]. The simulation clock was halted one hour prior to the known
situation (congested or not), and predictive indicators were evaluated.
This paper documents the successful discovery of a congestion prediction
indicator.
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