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dc.contributor.authorBoulagouas, Wafa
dc.contributor.authorGarcía Herrero, Susana 
dc.contributor.authorChaib, Rachid
dc.contributor.authorFebres Eguiguren, Juan Diego
dc.contributor.authorMariscal Saldaña, Miguel Ángel 
dc.contributor.authorDjebabra, Mébarek
dc.date.accessioned2024-04-22T10:50:06Z
dc.date.available2024-04-22T10:50:06Z
dc.date.issued2020-09
dc.identifier.issn1660-4601
dc.identifier.urihttp://hdl.handle.net/10259/9016
dc.description.abstractRoad traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.en
dc.description.sponsorshipThis work started with funds from the Dirección General de Tráfico (DGT) for the Project “Modelo Cuantitativo de Red Bayesiana con capacidad predictiva de la gravedad del accidente en función de los comportamientos y actuaciones de las personas”, ref. SPIP2015-1852 and pursued with research project “Modelización mediante técnicas de machine learning de la influencia de las distracciones del conductor en la seguridad vial. Diseño de un sistema integrado: simulador de conducción, eye tracker y dispositivo de distracción. Ref. BU300P18” supported by funds from FEDER (Fondo Europeo de Desarrollo Regional - Junta de Castilla y León).en
dc.language.isoenges
dc.publisherMDPIen
dc.relation.ispartofInternational Journal of Environmental Research and Public Health. 2020, V. 17, n. 18, 6743en
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectAlignmenten
dc.subjectRegulatoryen
dc.subjectBehaviorsen
dc.subjectDriversen
dc.subjectBayesianen
dc.subjectNetworken
dc.subjectTrafficen
dc.subjectAccidentsen
dc.subjectUnlicenseden
dc.subjectUnsafeen
dc.subject.otherTransporteses
dc.subject.otherTransportationen
dc.subject.otherSaludes
dc.subject.otherHealthen
dc.titleAn Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurementen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.3390/ijerph17186743es
dc.identifier.doi10.3390/ijerph17186743
dc.identifier.essn1660-4601
dc.journal.titleInternational Journal of Environmental Research and Public Healthen
dc.volume.number17es
dc.issue.number18es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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