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Toward safer highways: predicting driver stress in varying conditions on habitual routes

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)es
dc.contributor.authorCorcoba Magaña, Víctores
dc.contributor.authorMuñoz Organero, Marioes
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.contributor.funderMinisterio de Educación, Cultura y Deporte (España)es
dc.date.accessioned2021-02-04T12:58:27Z
dc.date.available2021-02-04T12:58:27Z
dc.date.issued2017-12-01
dc.description.abstractDriver stress is a growing problem in the transportation industry. It causes a deterioration of cognitive skills, resulting in poor driving and an increase in the likelihood of traffic accidents. Prediction models allow us to avoid or at least minimize the negative consequences of stress. In this article, an algorithm based on deep learning is proposed to predict driver stress. This type of algorithm detects complex relationships among variables. At the same time, it avoids overfitting. The prediction of the upcoming stress level is made by taking into account driving behavior (acceleration, deceleration, speed) and the previous stress level.en
dc.description.sponsorshipThis work was supported by the “HERMES-SMART DRIVER” project TIN2013-46801-C4-2-R, funded by the Spanish Ministry of Economy, Industry and Competitiveness, from the grant PRX15/00036 from the Ministerio de Educación Cultura y Deporte, and from a sabbatical leave by the Carlos III University of Madrid.en
dc.description.statusPublicadoes
dc.format.extent7
dc.identifier.bibliographicCitationIEEE Vehicular Technology Magazine, (2017), 12(4), pp.: 69 - 76.en
dc.identifier.doihttps://doi.org/10.1109/MVT.2017.2692059
dc.identifier.issn1556-6072
dc.identifier.publicationfirstpage69
dc.identifier.publicationissue4
dc.identifier.publicationlastpage76
dc.identifier.publicationtitleIEEE Vehicular Technology Magazineen
dc.identifier.publicationvolume12
dc.identifier.urihttps://hdl.handle.net/10016/31863
dc.identifier.uxxiAR/0000026369
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDGobierno de España. TIN2013-46801-C4-2-Res
dc.relation.projectIDGobierno de España. PRX15/00036es
dc.rights© 2017 IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherPrediction algorithmsen
dc.subject.otherStress measurementen
dc.subject.otherHeart rate variabilityen
dc.subject.otherAccelerationen
dc.subject.otherVehicle safetyen
dc.subject.otherHuman factorsen
dc.titleToward safer highways: predicting driver stress in varying conditions on habitual routesen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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