Wind-Based Robust Trajectory Optimization using Meteorological Ensemble Probabilistic Forecasts

Conference object English UNKNOWN
González Arribas, Daniel ; Soler Arnedo, Manuel Fernando ; Sanjurjo Rivo, Manuel (2016)
  • Publisher: Eurocontrol
  • Subject: Aeronáutica

A major challenge for Trajectory-Based Operations is the existence of significant uncertainties in the models and systems required for trajectory prediction. In particular, weather uncertainty has been acknowledged as one of the most (if not the most) relevant ones. In the present paper we present preliminary results on robust trajectory planning at the pre-tactical level. The main goal is to plan trajectories that are efficient, yet predictable. State-of-the-art forecasts from Ensemble Prediction Systems are used as input data for the wind field, which we assume to be the unique source of uncertainty. We develop an ad-hoc optimal control methodology to solve trajectory planning problems considering uncertainty in wind fields. A set of Paretooptimal trajectories is obtained for different preferences between predictability and average efficiency; in particular, we present and discuss results for the minimum average fuel trajectory and the most predictable trajectory, including the trade-off between fuel consumption and time dispersion. We show how uncertainty can be quantified and reduced by proposing alternative trajectories. This work has been partially supported by project TBO-MET project (https://tbometh2020. com/), which has received funding from the SESAR JU under grant agreement No 699294 under European Union’s Horizon 2020 research and innovation programme. This work is also partially supported by the Spanish Government through Project entitled Analysis and optimisation of aircraft trajectories under the effects of meteorological uncertainty (TRA2014-58413-C2-2-R). The project has been funded under RD&I actions of Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad (call 2014). European Commission
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