GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration

• URL: http://arxiv.org/abs/2307.15876v1
• Date: Sat, 29 Jul 2023 03:04:22 GMT
• Title: GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration
• Authors: Ke Feng, Dahai Liu, Yongxin Liu, Hong Liu, Houbing Song
• Abstract summary: The National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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.
• Score: 24.461948296296274
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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

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