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This content will become publicly available on August 7, 2024

Title: A Graph-Analytic Approach to Dynamic Airspace Configuration
The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning. This study proposes a more dynamic airspace configuration (DAC) approach that could increase throughput and accommodate fluctuating traffic, ideal for emergencies. The proposed approach constructs the airspace as a constraints-embedded graph, compresses its dimensions, and applies a spectral clustering-enabled adaptive algorithm to generate collaborative airport groups and evenly distribute workloads among them. Under various traffic conditions, our experiments demonstrate a 50% reduction in workload imbalances. This research could ultimately form the basis for a recommendation system for optimized airspace configuration. Code available at https://github.com/KeFenge2022/GraphDAC.git  more » « less
Award ID(s):
2142514
NSF-PAR ID:
10467134
Author(s) / Creator(s):
; ; ; ;
Editor(s):
Cristina Ceballos
Publisher / Repository:
IEEE Computer Society Conference Publishing Services (CPS) http://www.computer.org/cps
Date Published:
ISSN:
2835-5776
Page Range / eLocation ID:
235 - 241
Subject(s) / Keyword(s):
["Dynamic Airspace Configuration, Graph Analytic, Singular Value Decomposition, Antoencoder"]
Format(s):
Medium: X
Location:
Seattle, Washington
Sponsoring Org:
National Science Foundation
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