The ATC Planned Trajectories will be improved thanks to the usage of Aircraft Data (new ADS-C reports and Surveillance parameters from Mode-S & ADS-B) and eFPL data. This data provides useful hints to the ATC system about high-level Airspace User navigation strategy/preferences on how to close the degrees of freedom. In particular: which are the FMS preferred manoeuvres (among all the possible ones) to follow the FMS known route and restrictions. Then, the ATC system will take into account those high-level preferences to make better assumptions on the preferred manoeuvres to follow the ground current view of the route and restrictions (which, in most cases, will include some discrepancies when compared to the FMS ones). In addition, the ATC system will have a more precise view on aircraft current conditions, improving the accuracy of its calculations.
The following data will be considered:
¿ Current gross mass of the A/C, to improve predictions of A/C performances.
¿ A/C preferred speeds per flight phase, as well as A/C predicted speeds in cruise points to improve ETO calculation and predictions of aircraft performance-limited vertical maneuvers.
¿ Predicted TopOfClimb and TopOfDescent points, allowing a better identification of the aircraft perceived climb/cruise/descent phases scope, and so, allowing a better selection of the scheduled speed to be used
¿ Current A/C speed, to deduce selected speeds and/or de-facto preferred speeds for all flights (even if not ATN B2 equipped).
Additionally, the ATC Planned Trajectories will be improved thanks to a default better modelling of common aircraft preferences during the descent phase, concerning:
¿ Catch-up manoeuvres from current position to the optimal descent profile
¿ Geometric manoeuvres in-between consecutive descending restrictions
|ER APP ATC 167||
IOC - FOC
|ER APP ATC 167||ATC Planned Trajectories improvement with new ADS-C reports, eFPL and surveillance information.||Analysis|
|PJ.18-06a||Air Traffic Control (ATC) Planned Trajectory Performance Improvement||SESAR 2020 Wave 1||Analysis|