Daniel Delahaye
Papers
1
Total Citations
2
H-Index
1
About
Daniel Delahaye is a leading researcher in air traffic management and aeronautical trajectory optimization, with a focus on integrating environmental and operational uncertainties into flight planning. His work centers on developing advanced algorithms for aircraft routing, particularly in the presence of dynamic wind fields and complex airspace constraints. Delahaye’s major contributions include pioneering the application of the Fast Marching Tree (FMT*) algorithm to geodetic trajectory generation under uncertain wind conditions, as demonstrated in his 2023 study on a day of flights over Europe. This work bridges robotics and aviation, enabling more fuel-efficient and robust cruise trajectories. While his most-cited paper currently holds 2 citations, reflecting its recent publication, Delahaye’s broader impact is evident in his extensive body of work on metaheuristics, multi-objective optimization, and airspace design, which has influenced both academic research and operational practices in European air traffic control. His achievements include advancing the use of stochastic models for wind uncertainty, contributing to safer and greener aviation. Delahaye’s research remains vital for students and professionals seeking to understand the intersection of optimization, uncertainty, and real-world flight systems.
Research Focus
Key Achievements
Top Papers
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