This project was carried through in the scope of my Applied Artificial Intelligence MSc at Cranfield University. It was made on the proposal of NATS, the UK's leading provider of air traffic control services.
Originally, NATS gave a broad description for the project: My goal was to investigate opportunities to reduce the amount of communcations in the current air traffic system, as these are expected to grow exponentially in the near future, mainly because of the arrival of drones and other UAVs in the air traffic system (ATS).
After some extensive research on the current state of the ATS, I took inspiration from the DeepTP project by Yulin Liu (https://github.com/yulinliu101/DeepTP) for the next steps of the project
This project is made up of two main parts:
- The implementation of an artificial neural network for aircraft trajectory prediction using weather data
- The simulation of a communication reduction framework, in order to limit the frequency of air-ground communication
The main file is the Python Notebook, while the implementation of the neural network and the data handling are located in .py files. You can also find the Powerpoint Presentations on the "IRP ppt" folder for more insight on the different steps that the project went through.