Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/16886
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dc.contributor.authorGarrido, R.-
dc.contributor.authorBastos, A.-
dc.contributor.authorde Almeida, A.-
dc.contributor.authorElvas, J. P.-
dc.date.accessioned2018-12-07T09:38:21Z-
dc.date.available2018-12-07T09:38:21Z-
dc.date.issued2014-
dc.identifier.issn2352-1465-
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-31549-
dc.identifier.urihttp://hdl.handle.net/10071/16886-
dc.descriptionWOS:000377412600024-
dc.description.abstractThe ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men.eng
dc.language.isoeng-
dc.publisherElsevier-
dc.relationTICE.Mobilidade-
dc.rightsopenAccess-
dc.subjectRoad safetyeng
dc.subjectRoad accident modellingeng
dc.subjectInjury severityeng
dc.subjectMotor-vehicle occupantseng
dc.subjectOrdered probit modeleng
dc.titlePrediction of road accident severity using the ordered probit modeleng
dc.typeconferenceObject-
dc.event.typeConferênciapt
dc.event.date2017-
dc.pagination214 - 223-
dc.peerreviewedyes-
dc.journalTransportation Research Procedia-
dc.volume3-
degois.publication.firstPage214-
degois.publication.lastPage223-
degois.publication.titlePrediction of road accident severity using the ordered probit modeleng
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
dc.identifier.doi10.1016/j.trpro.2014.10.107-
Appears in Collections:CTI-CRI - Comunicações a conferências internacionais

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