Research


Research interests

  • Urban air mobility
  • Airspace design
  • Air traffic complexity
  • Air traffic flow management
  • Aircraft conflict detection and resolution
  • 4D trajectory prediction
  • Data analysis
  • Machine learning

Research projects

Adaptive structuring of unmanned traffic: A UTM concept (2019 - 2022), Funded by research project CONCORDE of the Defense Innovation Agency (AID) of the French Ministry of Defense (2019650090004707501)

The objective of this project is to propose solutions for the organization of large-scale drone traffic that maximizes the use of airspace while respecting the constraints of civil air traffic. Such planning will automatically structure UAV into flows in order to increase the overall airspace capacity. Such flow structuring will be also applied in a dynamical way.

Data-driven conflict detection enhancement for en-route operations (2019 - 2020), Optim group, ENAC

In this project, we investigates how to accurately determine the distance and time of closest approach between flights in the en-route phase by using machine learning algorithms with mode-S data. Such results will be used to assist mid-term conflict detection with the lookahead time of 5-20 minutes.

4D trajectory prediction with machine learning models (2017 - 2019), Optim group, ENAC

This project aims to improve the operational efficiency and the predictability of air traffic by short-term trajectory prediction in terminal manoeuvring area by application of machine learning methods.