Sensitivity of Trajectory Prediction Accuracy to Aircraft Performance Uncertainty

The global Air Traffic Management (ATM) system is being transformed to enable increased capacity, efficiency and safety while contributing to reduce the environmental impact of aviation. A key element of this transformation is the introduction of TrajectoryBased Operations (TBO), which rely on advanced computer-based automation and digital data communications to enable airspace users and Air Navigation Service Providers (ASNPs) to collaboratively and strategically manage the aircraft’s intended trajectory. In the context of TBO, airborne and ground-based automation systems will predict trajectories and exchange trajectory information, both pre-departure and during the fight, to support a process aimed at assigning each aircraft a trajectory that achieves a compromise between the preferences of the airspace user and the constraints imposed by Air Traffic Control (ATC). It is anticipated that the automation infrastructure required to support TBO will require sophisticated trajectory prediction capabilities to accurately estimate the intended trajectory of the aircraft in different operational contexts and environmental conditions and for different look-ahead times. Such trajectory predictors will in turn need precise aircraft performance information to calculate the trajectory, in addition to other data such as wind and temperature forecasts, initial aircraft state or aircraft intent. This paper proposes a methodology to assess the impact on trajectory prediction accuracy of the aircraft performance uncertainty derived from the use of parametric models such as BADA. The proposed method, based on statistical modeling, enables the definition of performance uncertainty bounds for all aircraft of the same type and of the resulting bounds in trajectory prediction error.