DIAPASON

DESCRIPTION

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.