Towards Greener and Smarter Airspace: Data-Driven Trajectory and Traffic Flow Optimisation

Abstract

The rapid growth in air transportation, coupled with limited airspace capacity, has led to escalating challenges including congestion, delays, economic inefficiencies, and environmental impacts. In this seminar, Dr Chunyao Ma will share her recent research on enabling smarter and greener airspace operations through data-driven optimisation techniques. This seminar will present recent advances in data-driven strategies for smarter and greener airspace optimisation, including descent trajectory optimisation and en-route traffic flow coordination, emphasising the integration of network theory and state-of-the-art machine learning techniques. These include transformer neural networks, reinforcement learning, and confident learning. Her work aims to enable more efficient, sustainable, and conflict-free operations through predictive and adaptive air traffic management solutions.

Speaker

Dr Chunyao Ma is a Research Fellow at Nanyang Technological University (NTU), Singapore. She received her PhD from NTU in 2023, with a research focus on data-driven air traffic flow optimisation and prediction. Her current work centers on enabling sustainable and efficient air traffic operations through machine learning and network-based methods. She is leading an industrial collaboration project with Thales AIR Lab Singapore on interaction-free continuous descent operations, aiming to reduce fuel burn and emissions. In addition, she leads NTU’s participation in the SESAR-funded DeepFlow project, which develops a flow-centric air traffic coordination framework in collaboration with leading European aviation partners.