Towards Safe and Intelligent Air Traffic Operations

Air Transportation Modeling and Control Laboratory (ATMCL, Principal Investigator: Professor Keumjin Lee) conducts research on air traffic management (ATM), developing data-driven modeling and optimization methods for safer and more efficient aircraft operations, such as air traffic flow management, flgiht trajectory prediction, free route airspace, and advanced ATM technologies. ATMCL also studies unmanned traffic management (UTM), aiming to ensure safe low-altitude operations through geofencing, path planning, conflict management, and risk assessment frameworks.

Seonggin Lee is honored with an Excellence Award at the Veterans Startup Competition hosted by the Ministry of Patriots and Veterans Affairs, South Korea, for his AI-driven Aviation startup. Huge congratulations!

The paper “Aircraft Trajectory Dataset Augmentation in Latent Space” by Seokbin Yoon and Keumjin Lee is accepted at International Journal of Aeronautical and Space Sciences. Congrats!

Honga Chai presents research on “Learning to Explain Air Traffic Situation,” co-authored with Seokbin Yoon and Keumjin Lee, at the First US–Europe Air Transportation R&D Symposium in Prague, Czech Republic. Well done!

Juyoung Kim and Juhong Kim have successfully graduated with Master’s degrees. Their thesis titles are “A Study on UAM Traffic Flow Based on Cellular Automaton” and “Data-driven Approach to Determine Maximum Drone Flight Altitudes in Airport Control Zones.” Huge Congrats!

The paper “Aircraft Trajectory Prediction with Inverted Transformer” by Seokbin Yoon and Keumjin Lee is accepted at IEEE Access. Congrats!