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dc.contributor.authorOña López, Juan José De 
dc.contributor.authorLópez Maldonado, Griselda
dc.contributor.authorAbellán Mulero, Joaquín 
dc.date.accessioned2013-04-09T06:15:15Z
dc.date.available2013-04-09T06:15:15Z
dc.date.issued2013
dc.identifier.citationOña, J.; López, G.; Abellán, J. Extracting decision rules from police accident reports through decision trees. Accident Analysis and Prevention 50: 1151–1160 (2013). [http://hdl.handle.net/10481/24425]es_ES
dc.identifier.issn0001-4575
dc.identifier.otherdoi: 10.1016/j.aap.2012.09.006
dc.identifier.urihttp://hdl.handle.net/10481/24425
dc.description.abstractGiven the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules.es_ES
dc.description.sponsorshipTRYSE Research Group, Department of Civil Engineering, University of Granada, Spaines_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.subjectTraffic accidentes_ES
dc.subjectSeverityes_ES
dc.subjectDecision treeses_ES
dc.subjectCART (Classification and Regression Tree)es_ES
dc.subjectC4.5es_ES
dc.subjectDecision ruleses_ES
dc.titleExtracting decision rules from police accident reports through decision treeses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.aap.2012.09.006es_ES


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