GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration

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2307.15876.pdf (2.2 MB)

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https://arxiv.org/abs/2307.15876

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https://doi.org/10.48550/arXiv.2307.15876
 http://hdl.handle.net/11603/29288

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UMBC Information Systems Department
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https://orcid.org/0000-0003-2631-9223

Date

2023-07-29

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journal articles
preprints
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication

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Abstract

The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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.