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A Methodology for Driving Behavior Recognition in Simulated Scenarios Using Biosignals

dc.contributor.editorFigueroa-Garcia J.C.
dc.contributor.editorDuarte-Gonzalez M.
dc.contributor.editorJaramillo-Isaza S.
dc.contributor.editorOrjuela-Canon A.D.
dc.contributor.editorDiaz-Gutierrez Y.
dc.creatorDomínguez Jiménez, Juan Antonio
dc.creatorCampo Landines, Kiara
dc.creatorContreras Ortiz, Sonia Helena
dc.date.accessioned2020-03-26T16:33:06Z
dc.date.available2020-03-26T16:33:06Z
dc.date.issued2019
dc.identifier.citationCommunications in Computer and Information Science; Vol. 1052, pp. 357-367
dc.identifier.isbn9783030310189
dc.identifier.issn18650929
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9167
dc.description.abstractThe recognition of aggressive driving patterns could aid to improve driving safety and potentially reduce traffic fatalities on the roads. Driving behavior is strongly shaped by emotions and can be divided into two main categories: calmed (non-aggressive) and aggressive. In this paper, we present a methodology to recognize driving behavior using driving performance features and biosignals. We used biosensors to measure heart rate and galvanic skin response of fifteen volunteers while driving in a simulated scenario. They were asked to drive in two different situations to elicit calmed and aggressive driving behaviors. The purpose of this study was to determine if driving behavior can be assessed from biosignals and acceleration/braking events. From two-tailed student t-tests, the results suggest that it is possible to differentiate between aggressive and calmed driving behavior from biosignals and also from longitudinal vehicle’s data. © 2019, Springer Nature Switzerland AG.eng
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075688427&doi=10.1007%2f978-3-030-31019-6_31&partnerID=40&md5=f7ed101058fc2d5b7a15c0fe2962c40c
dc.titleA Methodology for Driving Behavior Recognition in Simulated Scenarios Using Biosignals
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datacite.rightshttp://purl.org/coar/access_right/c_16ec
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.source.event6th Workshop on Engineering Applications, WEA 2019
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1007/978-3-030-31019-6_31
dc.subject.keywordsAcceleration patterns
dc.subject.keywordsBiosignals
dc.subject.keywordsDriving behavior
dc.subject.keywordsFeature extraction
dc.subject.keywordsAutomobile drivers
dc.subject.keywordsDigital storage
dc.subject.keywordsElectrophysiology
dc.subject.keywordsFeature extraction
dc.subject.keywordsTraffic surveys
dc.subject.keywordsAcceleration pattern
dc.subject.keywordsAggressive driving
dc.subject.keywordsAggressive driving behaviors
dc.subject.keywordsBiosignals
dc.subject.keywordsDriving behavior
dc.subject.keywordsDriving performance
dc.subject.keywordsGalvanic skin response
dc.subject.keywordsTraffic fatalities
dc.subject.keywordsBehavioral research
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.relation.conferencedate16 October 2019 through 18 October 2019
dc.type.spaConferencia
dc.identifier.orcid56682770100
dc.identifier.orcid57205565967
dc.identifier.orcid57210822856


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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.