A multi-agent reinforcement learning approach for flight speed control systems
With increasing air traffic, there is an ever-growing need for Air Traffic Controllers (ATCO) to efficiently manage air traffic and congestion. Congestion often leads to increase in delays in the Terminal Maneuvering Area (TMA), which is one of the primary challenges that is being faced by ATCO. Int...
Saved in:
Main Author: | Kanupriya, Malhotra |
---|---|
Other Authors: | Sameer Alam |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/159164 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
A multi-agent reinforcement learning approach for system-level flight delay absorption
by: Malhotra, Kanupriya, et al.
Published: (2023) -
Investigation and modeling of flight technical error (FTE) associated with UAS operating with and without pilot guidance
by: Wang, John Chung-Hung, et al.
Published: (2021) -
Optimisation of operation flight plan using genetic algorithm
by: Loh, Kai Leong.
Published: (2011) -
A machine learning approach on past ADS-B data to predict planning controller’s actions
by: Pham, Duc-Thinh, et al.
Published: (2021) -
An air traffic controller action extraction-prediction model using machine learning approach
by: Pham, Duc-Thinh, et al.
Published: (2021)