SynthAIr - Generating Synthetic Aircraft Trajectories - Poster
Year: 2024
Type: article
Abstract: SynthAIr aims to enhance ATM automation and simulation through AI- driven synthetic data generation, exploring six interconnected use cases. This work focuses on Use Case 4, generating synthetic aircraft trajectories. Why Do Synthetic Trajectories Matter? • Enhance simulations with diverse and realistic scenarios. • Augment existing data to improve machine learning model training. • Safely test new ATM concepts and strategies. • Address data scarcity while maintaining privacy. • Support capacity planning with data-driven insights. • Explore rare events without introducing operational risks. • Expand limited datasets for comprehensive airspace analysis.
Authors: SINTEF, Delft University of Technology, Eurocontrol, Deep Blue (Italy)
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930704939
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