A data-driven framework for modelling complexity in terminal manoeuvring area

• Main Authors: Lim, Zhi Jun, Dhief, Imen, Pham, Duc-Thinh, Alam, Sameer, Delahaye, Daniel
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Engineering; Air traffic management; Terminal manoeuvring area; Complexity; Data-driven; Unsupervised machine learning; Clustering
• Online Access: https://hdl.handle.net/10356/181825; https://www.sesarju.eu/SIDS2024

This paper presents an objective, data-driven framework for quantifying air traffic complexity in the Terminal Manoeuvring Area (TMA) using historical ADS-B data from Singapore TMA. The motivation for developing this framework stems from the limitations of traditional subjective measures, which are...