Optimal Aircraft Trajectory Planning in the Presence of Stochastic Convective Weather Cells

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dc.contributor.author González Arribas, Daniel
dc.contributor.author Hentzen, Daniel
dc.contributor.author Sanjurjo Rivo, Manuel
dc.contributor.author Soler Arnedo, Manuel Fernando
dc.contributor.author Kamgarpour, Maryam
dc.date.accessioned 2017-06-30T09:15:28Z
dc.date.available 2018-06-30T22:00:05Z
dc.date.issued 2017-06
dc.identifier.bibliographicCitation 17th AIAA Aviation Technology, Integration, and Operations Conference, AIAA AVIATION Forum, Denver, Colorado. AIAA 2017-3431, pp. 1-13.
dc.identifier.uri http://hdl.handle.net/10016/24724
dc.description.abstract The Air Traffic Management system is heavily influenced by meteorological uncertainty, and convective weather cells represent one of the most relevant uncertain meteorological phenomena. They are weather hazards that must be avoided through tactical trajectory modifications. As a consequence of the existence in uncertainty in meteorological forecasts and nowcasts, it is important to consider the convective weather cells to be avoided as a stochastic, time-dependent process. In this paper we present a comparative analysis of two methodologies for handling stochastic storms in trajectory planning: one based on stochastic reachability and a second one, based on robust optimal control. In the former, the thunderstorm avoidance problem is modelled as a stochastic reach-avoid problem, considering the motion of the aircraft as a discrete-time stochastic system and the weather hazards as random set-valued obstacles. Dynamic programming is used to compute a Markov feedback policy that maximizes the probability of reaching the target before entering the unsafe set, i.e., the hazardous weather zones. For the latter, the stochastic dynamics of the storms are modeled in continuous time. We implement an optimal control formulation that allows different possible realizations of the stochastic process to be considered. The resulting problem is then transcribed to a nonlinear programming (NLP) problem through the use of direct numerical methods. A benchmark case study is presented, in which the effectiveness of the two proposed approaches are analyzed.
dc.description.sponsorship 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. 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).
dc.description.sponsorship European Commission
dc.format.extent 13
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher American Institute Of Aeronautics And Astronautics (AIAA)
dc.relation.ispartofseries AIAA AVIATION Forum
dc.rights © The American Institute of Aeronautics and Astronautics, 2017
dc.title Optimal Aircraft Trajectory Planning in the Presence of Stochastic Convective Weather Cells
dc.type bookPart
dc.type conferenceObject
dc.subject.eciencia Aeronáutica
dc.identifier.doi https://dx.doi.org/10.2514/6.2017-3431
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/699294
dc.relation.projectID Gobierno de España. TRA2014-58413-C2-2-R
dc.type.version acceptedVersion
dc.relation.eventdate 05-09 de junio de 2017
dc.relation.eventplace Denver, Colorado (Estados Unidos)
dc.relation.eventtitle 17th AIAA Aviation Technology, Integration, and Operations Conference
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 3431-1
dc.identifier.publicationlastpage 3431-13
dc.identifier.publicationtitle 17th AIAA Aviation Technology, Integration, and Operations Conference, AIAA AVIATION Forum. Denver, Colorado
dc.identifier.uxxi CC/0000027179
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