Incremental, Probabilistic Decision Making for En Route Traffic Management
November 2007
Craig Wanke, The MITRE Corporation
Daniel Greenbaum, The MITRE Corporation
ABSTRACT
En route airspace congestion, often due to
convective weather, causes system-wide delays and
disruption in the U.S. National Airspace System
(NAS). Today's methods for managing congestion
are mostly manual, based on uncertain forecasts of
weather and traffic demand, and often involve
rerouting or delaying entire flows of aircraft. A
new, incremental decision-making approach is
proposed, in which prediction uncertainty is
explicitly used to develop effective and efficient
congestion resolution actions. Decisions are made
based on a quantitative evaluation of the expected
delay cost distribution, and resolution actions are
targeted at specific flights, rather than flows. A
massively-parallel simulation of the proposed
method has been developed, and results for an
operational-scale congestion problem are presented.
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