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Aerospace 2019, 6(2), 15; https://doi.org/10.3390/aerospace6020015

Interdependent Uncertainty Handling in Trajectory Prediction

Chair of Air Transport Technology and Logistics, Technische Universität Dresden, 01069 Dresden, Germany
These authors contributed equally to this work.
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Received: 8 December 2018 / Revised: 19 January 2019 / Accepted: 4 February 2019 / Published: 12 February 2019
(This article belongs to the Collection Air Transportation—Operations and Management)
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Abstract

The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties have to be modeled properly and considered in decision support tools for efficient air traffic flow management. Therefore, the subjacent causes for uncertainties, their effects on the aircraft trajectory and their dependencies to each other must be understood in detail. Besides the atmospheric conditions as the main external cause, the aircraft itself induces uncertainties to its trajectory. In this study, a cause-and-effect model is introduced, which deals with multiple interdependent uncertainties with different stochastic behavior and their impact on trajectory prediction. The approach is applied to typical uncertainties in trajectory prediction, such as the actual take-off mass, non-constant true air speeds, and uncertain weather conditions. The continuous climb profiles of those disturbed trajectories are successfully predicted. In general, our approach is applicable to all sources of quantifiable interdependent uncertainties. Therewith, ground-based trajectory prediction can be improved and a successful implementation of trajectory-based operations in the European air traffic system can be advanced. View Full-Text
Keywords: trajectory prediction; uncertainty handling; model-based simulation; stochastic modelling; automation in ATM; flight performance; actual take-off mass trajectory prediction; uncertainty handling; model-based simulation; stochastic modelling; automation in ATM; flight performance; actual take-off mass
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zeh, T.; Rosenow, J.; Fricke, H. Interdependent Uncertainty Handling in Trajectory Prediction. Aerospace 2019, 6, 15.

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