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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/24425

Title: Extracting decision rules from police accident reports through decision trees
Authors: Oña, Juan de
López Maldonado, Griselda
Abellán, Joaquín
Issue Date: 2013
Abstract: Given 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.
Sponsorship: TRYSE Research Group, Department of Civil Engineering, University of Granada, Spain
Publisher: Elsevier
Keywords: Traffic accident
Decision trees
CART (Classification and Regression Tree)
Decision rules
URI: http://hdl.handle.net/10481/24425
ISSN: 0001-4575
Citation: Oña, 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]
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