The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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
@article{arxiv.2307.15876,
title = {GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration},
author = {Ke Feng and Dahai Liu and Yongxin Liu and Hong Liu and Houbing Song},
journal= {arXiv preprint arXiv:2307.15876},
year = {2023}
}