Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/13201
Robust flight planning impact assessment considering convective phenomena
Title: Robust flight planning impact assessment considering convective phenomena
Authors: García-Heras, JavierSoler, ManuelGonzález Arribas, DanielEschbacher, KurtRokitansky, Carl-HerbertSacher, DanielGelhardt, UlrikeLang, JürgenHauf, ThomasSimarro, Juan Pablo ORCID SCOPUSID Autor AEMETValenzuela, AlfonsoFranco, AntonioRivas, Damián
Keywords: Robust flight-planning; Convective weather; Simulation
Issue Date: 2021
Publisher: Elsevier
Citation: Transportation Research Part C: Emerging Technologies. 2021, 123, 102968
Publisher version: https://doi.org/10.1016/j.trc.2021.102968
Abstract: Thunderstorms are one of the leading causes of Air Traffic Management delays. In this paper, we assess how incorporating convective information into flight planning algorithms can lead to reductions in reroutings due to storm encounters during the execution of the flight. We use robust open-loop optimal control methodology at the flight planning level and incorporate meteorological uncertainties based on Ensemble Prediction System forecasts. Convective risk areas can be derived from the latter to be included in the objective function. At the execution level, the planned trajectories are included in an air traffic simulator (NAVSIM) under observed weather (wind and storms). In this simulation process, track modifications might be triggered in case of encountering an observed thunderstorm. A tool termed DIVMET based on pathfinding algorithms has been integrated into NAVSIM is considered to that end. Results show that planning robust trajectories (avoiding thus convective areas) reduces the number of storms encounters and increases predictability. This increase in predictability is at a cost in terms of fuel and time, also quantified.
Sponsorship : This work has been supported by TBO-MET project (https://tbomet-h2020.com/) which has received funding from the SESAR JU under grant agreement No 699294 under EU’s Horizon 2020 research and innovation programme.
URI: http://hdl.handle.net/20.500.11765/13201
ISSN: 0968-090X
Appears in Collections:Artículos científicos 2019-2022


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