The prediction of future air traffic situations is central to ATC planning. Its uses range from Air Traffic Controller workload management to ensure capacity, to helping the setup flow management measures in case the demand cannot be accommodated.
Different methods are used to generate forecasts for different time horizons to support relevant decisions; the basic question always being ‘how can the demand be met?’ Long-term answers might be ‘build a new control centre’, ‘train some new controllers’ and so on. The medium-term question might be answered by managing the controller leave roster and planning the ‘sector opening scheme’. The time-frame of main concern of this work is the ATC planning horizon (about 90 mins), with a mix of activated airborne flights (RBT available) and flights still in planning (SBT available). It is however intended that the scheme developed in this work will be generally applicable to all time-frames.
Trajectory Based Operations brings together many different improvements that allow the uncertainty of trajectory prediction to be better managed and reduced. These include downlinking of the Extended Projected Profile from the flight to enrich ground trajectory predictions, sharing of detailed information on the ground through SWIM (IOP), the submission of more detailed flight plan information, the use of 4D contracts during the flight, increasing adoption of Airport CDM, and so on.
For a given location, a prediction of the traffic that will cross it at some moment in the future is a mix of trajectories of flights which are airborne, flights that have been filed but not yet taken off and flight plans that have not yet been filed. Each type of flight has a different level of uncertainty or level of inaccuracy with which the prediction can be made. Current systems and operational processes mostly rely on human judgement and experience to deal with this mix of uncertainty. The result is often that a very imprecise balance is struck between demand and capacity leading to capacity going unused or significant last minute adjustments needing to be made.
In this context, the main concepts defined, modelled and studied by COPTRA are the notions of probabilistic trajectories and traffic situations. The central idea researched is to develop new methods to build the probabilistic traffic prediction by combining the probabilistic trajectories.
Building on the considerable inter-disciplinary expertise in trajectory prediction, applied mathematics and ATC planning accumulated by the project partners, COPTRA proposes an operational concept where the uncertainty of the predicted trajectories (hopefully reduced in TBO) is made explicit at trajectory prediction level and combined using state of the art applied mathematics methods to build a probabilistic traffic situation (i.e. traffic situation where the uncertainty is identified and specifically accounted for). These probabilistic traffic situations will be used to improve the prediction of occupancy counts used in ATC Planning and convey better information to the human operator.
