Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 40, Issue 15, Pages 6047-6054Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.05.027
Keywords
Traffic accident; Severity; Road safety; Decision Trees; Decision Rules
Categories
Funding
- Regional Ministry of Economy
- Innovation and Science of the regional government of Andalusia (Spain)
- Spanish General Directorate of Traffic (DGT)
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A Decision Tree (DT) is a potential method for studying traffic accident severity. One of its main advantages is that Decision Rules (DRs) can be extracted from its structure. And these DRs can be used to identify safety problems and establish certain measures of performance. However, when only one DT is used, rule extraction is limited to the structure of that DT and some important relationships between variables cannot be extracted. This paper presents a more effective method for extracting rules from DTs. The method's effectiveness when applied to a particular traffic accident dataset is shown. Specifically, our study focuses on traffic accident data from rural roads in Granada (Spain) from 2003 to 2009 (both included). The results show that we can obtain more than 70 relevant rules from our data using the new method, whereas with only one DT we would have extracted only five relevant rules from the same dataset. (C) 2013 Elsevier Ltd. All rights reserved.
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