A generative adversarial imitation learning approach for realistic aircraft taxi-speed modelling

A generative adversarial imitation learning approach for realistic aircraft taxi-speed modelling

Classical approaches for modeling aircraft taxi speed assume constant speed or use a turning rate function to approximate taxi timings for taxiing aircraft. However, those approaches cannot predict the Spatio-temporal component of aircraft-taxi trajectory due to a lack of consideration of the comple...

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Bibliographic Details
Main Authors: Pham, Duc-Thinh, Tran, Thanh-Nam, Alam, Sameer, Duong, Vu N.
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2021
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
Engineering::Aeronautical engineering::Flight simulation
Generative Adversarial Imitation Learning
Aircraft Ground Movement
Online Access:https://hdl.handle.net/10356/152909

Internet

https://hdl.handle.net/10356/152909

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