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Optimal Aircraft Trajectory Planning in Stochastic Environment


D. Hentzen

Semester Thesis, SS17

Meteorological uncertainty poses a major challenge in aircraft traffic management (ATM), in particular convective weather cells, which are responsible for up to half of airspace delay. With commercial air traffic on the rise and the risk of potentially critical capacity bottlenecks looming, it is vital that future trajectory planning tools are able to account for and quantify this uncertainty by characterizing them as stochastic, time-dependent processes. This work proposes an automated trajectory planning tool that allows aircraft to reach a specified target while avoiding hazardous weather regions, in particular convective storm cells. The generated trajectories are optimal with regard to both safety and reachability in the presence of process disturbances and uncertainty in the environment. To ensure the feasibility and performance of the optimization process, a stochastic model of the uncertainty inherent to the meteorological obstacles is derived. For this purpose, state-of-the-art nowcast data are analyzed and used in the optimal control problem. This also serves the purpose of investigating the algorithmís capability and scalability in real-world scenarios, especially with a view to a future implementation in trajectory-based air traffic operations. The quality of the generated forecasts and trajectories, as well as their suitability for use in both pre-tactical and tactical trajectory planning are analyzed.

Supervisors: Maryam Kampgarpour, Manuel Soler


Type of Publication:

(13)Semester/Bachelor Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2017:IFA_5682
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