fvalka/atc-reinforcement-learning
Reinforcement learning for an air traffic control task. OpenAI gym based simulation.
This project offers a way to train artificial intelligence (AI) to handle air traffic control tasks, specifically directing aircraft approaching an airport. It takes in simulated air traffic scenarios and outputs an AI that can guide planes to their final approach, aiming for improved efficiency, fuel savings, and reduced noise. Air traffic controllers, aviation researchers, and simulator developers could use this to explore new control strategies.
No commits in the last 6 months.
Use this if you are an aviation researcher or air traffic management professional looking to experiment with AI-driven approaches for optimizing aircraft approach control.
Not ideal if you need a full-scale, real-time air traffic control system for operational use, as this is a simulation and training environment.
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Last pushed
Dec 08, 2022
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