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Design of a speed assistant to minimize the driver stress

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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, Víctor
dc.contributor.authorMuñoz Organero, Mario
dc.contributor.authorÁlvarez-García, Juan Antonio
dc.contributor.authorFernández-Rodríguez, Jorge Yago
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.contributor.funderMinisterio de Educación, Cultura y Deporte (España)es
dc.date.accessioned2021-10-07T08:32:54Z
dc.date.available2021-10-07T08:32:54Z
dc.date.issued2017-01-23
dc.description.abstractStress is one of the most important factors in traffic accidents. When the driver is in this mental state, their skills and abilities are reduced. In this paper, we propose an algorithm to estimate the optimal speed to minimize stress levels on upcoming road segments when driving. The prediction model is based on deep learning. The stress level estimation considers the previous driver's driving behavior before reaching the road section to be assessed, the road state (weather and traffic), and the previous drives made by the driver. We use this algorithm to build a speed assistant. The solution provides an optimum average speed for each road segment that minimizes the stress. A validation experiment has been conducted in a real setting using two different types of vehicles. The proposal is able to predict the stress levels given the average speed by 84.20% on average. On the other hand, the speed assistant reduces the stress levels (estimated from the driver’s heart rate signal) and the aggressiveness of driving regardless of the vehicle type. The proposed solution is implemented on Android mobile devices and uses a heart rate chest strap.en
dc.description.sponsorshipThe research leading to these results has received funding from the «HERMES-SMART DRIVER/CITIZEN» projects TIN2013-46801-C4-2-R /1-R funded by the Spanish MINECO, from the grant PRX15/00036 from the Ministerio de Educación Cultura y Deporte.en
dc.format.extent12
dc.identifier.bibliographicCitationCorcoba Magaña, V., Muñoz Organero, M., Álvarez-García, J. A. & Fernández Rodríguez, J. Y. (2017). Design of a Speed Assistant to Minimize the Driver Stress. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 6(3), 45–56.en
dc.identifier.doihttps://doi.org/10.14201/ADCAIJ2017634556
dc.identifier.issn2255-2863
dc.identifier.publicationfirstpage45
dc.identifier.publicationissue3
dc.identifier.publicationlastpage56
dc.identifier.publicationtitleAdvances in Distributed Computing and Artificial Intelligence Journalen
dc.identifier.publicationvolume6
dc.identifier.urihttp://hdl.handle.net/10016/33381
dc.identifier.uxxiAR/0000022563
dc.language.isoeng
dc.publisherEdiciones Universidad de Salamancaes
dc.relation.projectIDGobierno de España. TIN2013-46801-C4-2-Res
dc.relation.projectIDGobierno de España. TIN2013-46801-C4-1-Res
dc.relation.projectIDGobierno de España. PRX15/00036es
dc.rights© Ediciones Universidad de Salamanca - CC BY.es
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherIntelligent transport systemen
dc.subject.otherDriver stressen
dc.subject.otherDriving assistanten
dc.subject.otherDeep learningen
dc.subject.otherParticle swarm optimizationen
dc.subject.otherAndroiden
dc.subject.otherMobile computingen
dc.titleDesign of a speed assistant to minimize the driver stressen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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