“A Data-drIven approach for dynamic and Adaptive trajectory PredictiON”


DIAPASON was part of the SESAR Engage KTN first Call for catalyst funding. The main DIAPASON objective was the development of a methodology for Trajectory Prediction (TP) and traffic forecasting in a pre-tactical phase (one day to six days before the day of operations), when few or no flight plans are available using a data-driven approach.

This has been adjusted to different time scales (planning horizons), taking into account the level of predictability of each of them. This initial step has been completed with a model that considers advanced tactical data to validate/enhance the previous pre-tactical prediction and incorporate “uncertainty” to TP (as a probabilistic approach).

DIAPASON was coordinated by CRIDA (Spain) and ZenaByte has been in charge of the development of the TP using Machine Learning.

This project has received funding from the SESAR Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 783287