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dc.contributor.authorTorres, Marina
dc.contributor.authorPelta Mochcovsky, David Alejandro 
dc.contributor.authorVerdegay Galdeano, José Luis 
dc.date.accessioned2024-01-25T12:20:11Z
dc.date.available2024-01-25T12:20:11Z
dc.date.issued2018-06-01
dc.identifier.urihttps://hdl.handle.net/10481/87303
dc.description.abstractPersonalization of pedestrian routes becomes a necessity due to the wide variety of user profiles that may differ on preferences or requirements to choose a route. Several software applications offer routes usually based on single criterion like distance or time; however, these criteria do not often fit the pedestrian needs. Here, we will first focus on the Personalized Routes Problem and then we will approach the specific case of designing accessible and green pedestrian routes. The proposal is implemented as a freely available Android application (named as PRoA, by intelligent multi-criteria Personalized Route Assistant), which automatically obtains geographical data and information for the decision criteria from open datasets. The proposal is evaluated using real cases at the city of Granada, Spain.es_ES
dc.description.sponsorshipResearch supported in part by projects TIN2014-55024-P (Spanish Ministry of Economy and Competitiveness) and P11-TIC-8001 (Consejería de Economía, Innovación y Ciencia, Junta de Andalucía). Both projects include FEDER funds from the European Union. M. Torres enjoys a Ph.D. research training staff grant associated with the project TIN2014-55024-P and co-funded by the European Social Fund .es_ES
dc.language.isoenges_ES
dc.publisherElsevier B.Ves_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.titlePRoA: An intelligent multi-criteria Personalized Route Assistantes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doihttps://doi.org/10.1016/j.engappai.2018.03.016


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