The current-day process for handling NAS element closure events (e.g., runways, taxiways, airspace sectors, and flight routes) involves frequently unilateral and uncoordinated decisions, disjointed sub-processes, and inefficient information exchanges, which can be significantly improved through advanced decision support technology.
ATAC’s NAS Element Closure Planner (NECP) applies state of the art machine learning techniques and combines them innovatively with proven airport-centric and NAS-wide traffic and airspace simulation tools, to develop a collaborative what-if analysis simulation-based decision support tool (DST). Probabilistic computations of expected future NAS states drive 1000s of simulations to enable efficient and comprehensive what-if evaluation of alternative future NAS element closure decisions (e.g., runway or taxiway closure start and end times, traffic rerouting and delay strategies).
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