Abstract
The existence of significant uncertainties in the models and systems required for trajectory prediction represents a major challenge for the Trajectory-Based Operations concept. Weather can be considered as one of the most relevant sources of uncertainty. Understanding and managing the impact of these uncertainties are necessary in order to increase the predictability of the ATM system. We present preliminary results on robust trajectory planning in which weather is assumed to be the unique source of uncertainty. State-of-the-art probabilistic forecasts from Ensemble Prediction Systems are employed to characterize uncertainty in the wind and potential convective areas. A robust optimal control methodology to produce efficient and predictable trajectories in the presence of these uncertainties is presented. A set of Pareto-optimal trajectories is obtained for different preferences between predictability, convective risk, and average efficiency.
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Notes
- 1.
TBO-MET project (https://tbomet-h2020.com/) has received funding from the SESAR JU under grant agreement No 699294 under EU’s Horizon 2020 research and innovation programme. Consortium members are UNIVERSITY OF SEVILLE (Coordinator), AEMET (Agencia Española de Meteorología), METEOSOLUTIONS GmbH, PARIS-LODRON-UNIVERSITAT SALZBURG, and UNIVERSIDAD CARLOS III DE MADRID.
- 2.
Attributable to National Weather Service Louisville, KY: http://www.weather.gov/lmk/indiceshttp://www.weather.gov/lmk/indices, accessed July 25, 2016.
- 3.
ECMWF, Reading, UK, accessed July 25, 2016:
http://www.ecmwf.int/en/research/modelling-and-prediction/atmospheric-physics http://www.ecmwf.int/en/research/modelling-and-prediction/atmospheric-physics.
- 4.
The \(\le \) sign applies in an element-wise fashion in Eq. (5) and analogous equations.
- 5.
Contrary to the usual definition, we take \(w_y\) to be in a South to North direction.
- 6.
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Acknowledgments
This work has been partially supported by project tbo-met project (https://tbomet-h2020.com/), which has received funding from the SESAR JU under grant agreement No 699294 under European Union’s Horizon 2020 research and innovation programme.
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González-Arribas, D. et al. (2019). Robust Optimal Trajectory Planning Under Uncertain Winds and Convective Risk. In: Electronic Navigation Research Institute (eds) Air Traffic Management and Systems III. EIWAC 2017. Lecture Notes in Electrical Engineering, vol 555. Springer, Singapore. https://doi.org/10.1007/978-981-13-7086-1_6
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DOI: https://doi.org/10.1007/978-981-13-7086-1_6
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