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

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Aeroespaciales
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Ingeniería Aeroespaciales
dc.contributor.authorGonzález Arribas, Daniel
dc.contributor.authorHentzen, Daniel
dc.contributor.authorSanjurjo Rivo, Manuel
dc.contributor.authorSoler Arnedo, Manuel Fernando
dc.contributor.authorKamgarpour, Maryam
dc.date.accessioned2017-06-30T09:15:28Z
dc.date.available2018-06-30T22:00:05Z
dc.date.issued2017-06
dc.description.abstractThe 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.en
dc.description.sponsorshipThis 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).en
dc.description.sponsorshipEuropean Commissionen
dc.format.extent13
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitation17th AIAA Aviation Technology, Integration, and Operations Conference, AIAA AVIATION Forum, Denver, Colorado. AIAA 2017-3431, pp. 1-13.
dc.identifier.doihttps://dx.doi.org/10.2514/6.2017-3431
dc.identifier.publicationfirstpage3431-1
dc.identifier.publicationlastpage3431-13
dc.identifier.publicationtitle17th AIAA Aviation Technology, Integration, and Operations Conference, AIAA AVIATION Forum. Denver, Coloradoen
dc.identifier.urihttps://hdl.handle.net/10016/24724
dc.identifier.uxxiCC/0000027179
dc.language.isoeng
dc.publisherAmerican Institute Of Aeronautics And Astronautics (AIAA)en
dc.relation.eventdate05-09 de junio de 2017es
dc.relation.eventplaceDenver, Colorado (Estados Unidos)es
dc.relation.eventtitle17th AIAA Aviation Technology, Integration, and Operations Conferenceen
dc.relation.ispartofseriesAIAA AVIATION Forumen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/699294
dc.relation.projectIDGobierno de España. TRA2014-58413-C2-2-Res
dc.rights© The American Institute of Aeronautics and Astronautics, 2017
dc.rights.accessRightsopen access
dc.subject.ecienciaAeronáuticaes
dc.titleOptimal Aircraft Trajectory Planning in the Presence of Stochastic Convective Weather Cellsen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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