Please use this identifier to cite or link to this item:
Title: Modelling aircraft priority assignment by air traffic controllers during taxiing conflicts using machine learning
Authors: Duggal, Vidurveer
Tran, Thanh-Nam
Pham, Duc-Thinh 
Alam, Sameer 
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
Issue Date: 2022
Source: Duggal, V., Tran, T., Pham, D. & Alam, S. (2022). Modelling aircraft priority assignment by air traffic controllers during taxiing conflicts using machine learning. Winter Simulation Conference 2022.
Conference: Winter Simulation Conference 2022
Abstract: Conflicts between taxiing aircraft are resolved by making the aircraft with lower priority wait, slow down, or change their path. Prevalent priority assignment is based on rules such as First Come First Serve. However, this is not viable as a priority assignment done by an air-traffic controller (ATC) based on multiple factors. Thus, a machine learning approach is proposed to mimic an ATC’s priority assignment. Firstly, the potential conflict scenarios between two aircraft from historical data, which are resolved, are detected and extracted. Then a Random Forest model is developed to learn ATC’s behaviors. The model mimics ATC’s behavior with an accuracy of 89% and can thus be an effective approach for priority assignment in path-planning and conflict resolution. Further analysis indicates that features such as unimpeded time difference, distance to destination and start, and speed are major considerations that affect the ATC’s decisions.
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Air Traffic Management Research Institute 
Rights: © 2022 Winter Simulation Conference. All rights reserved. This paper was published in Proceedings of the 2022 Winter Simulation Conference and is made available with permission of Winter Simulation Conference.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers
MAE Conference Papers

Files in This Item:
File Description SizeFormat 
WSC2022_Airport_Surface_Conflict_Resolution__Updated_.pdf1.68 MBAdobe PDFThumbnail

Page view(s)

Updated on Feb 26, 2024

Download(s) 50

Updated on Feb 26, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.