Using Decision Trees To Extract Decision Rules From Police Reports On Road Accidents

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Procedia - Social and Behavioral Sciences 53 (2012) 106 – 114

SIIV - 5th International Congress - Sustainability of Road Infrastructures

Using Decision Trees to extract Decision Rules from Police Reports on Road
Accidents
López Griseldaa*, de Oña Juanb and Abellán Joaquínc

a

Ph. D. Student. TRYSE Research Group. Department of Civil Engineering, University of Granada, ETSI Caminos, Canales y Puertos, c/Severo Ochoa s/n, 18071, Granada, Spain a Ph. D. TRYSE Research Group. Department of Civil Engineering, University of Granada, ETSI Caminos, Canales y Puertos, c/ Severo
Ochoa, s/n, 18071 Granada (Spain) c Ph. D. Department of Computer Science & Artificial Intelligence, University of Granada, ETSI Informática, c/Periodista Daniel
Saucedo Aranda s/n, 18071, Granada, Spain

Abstract
The World Health Organization (WHO) considers that traffic accidents are major public health problem worldwide, for this reason safety managers try to identify the main factors affecting the severity as consequence of road accidents. In order to identify these factors, in this paper, Data Mining (DM) techniques such as Decision Trees (DTs), have been used. A dataset of traffic accidents on rural roads in the province of Granada (Spain) have been analyzed.
DTs allow certain decision rules to be extracted. These rules could be used in future road safety campaigns and would enable managers to implement certain priority actions.
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1. Introduction
The World Health Organization (WHO) considers that traffic accidents are major public health problem worldwide that every year claiming 1.27 million

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