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GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration

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The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning.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

Data source:

Flight Delays and Cancellations were published by The U.S. Bureau of Transportation in 2015. This dataset is pulished on Kaggle: https://www.kaggle.com/datasets/usdot/flight-delays

To visulize the results, the FL airports location are inside the folder 'USA_Counties'.

Model and Experiments:

See file 'fl_cluster_color_balance_refined.py'

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