A supervised learning approach for 4D air traffic conflict prediction under trajectory uncertainty

A supervised learning approach for 4D air traffic conflict prediction under trajectory uncertainty

This paper presents a Supervised Learning approach for the problem of air traffic conflict prediction in 4- dimensional space (3-dimensional space and time) under trajectory uncertainties, resulting in non-nominal conflict points. Decision support systems for conflict prediction offer shortterm co...

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Bibliographic Details
Main Authors: Mohamed Arif Mohamed, Dang, Huu Phuoc, Alam, Sameer
Other Authors: 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Format: Conference Paper
Language:English
Published: 2023
Subjects:
Engineering
Air Traffic Control
Prediction
Online Access:https://hdl.handle.net/10356/170972
https://2023.ieee-itsc.org/

Internet

https://hdl.handle.net/10356/170972
https://2023.ieee-itsc.org/

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