A machine learning approach for conflict resolution in dense traffic scenarios with uncertainties

• Main Authors: Pham, Duc-Thinh, Tran, Ngoc Phu, Alam, Sameer, Duong, Vu, Delahaye, Daniel
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Aeronautical engineering; Air Traffic Command and Control; Reinforcement Learning
• Online Access: https://hdl.handle.net/10356/146568
• Institution: Nanyang Technological University

With the continuous growth in the air transportation demand, air traffic controllers will have to handle increased traffic and consequently more potential conflicts. This gives rise to the need for conflict resolution advisory tools that can perform well in high-density traffic scenarios given a noi...