期刊
SAFETY SCIENCE
卷 49, 期 10, 页码 1314-1320出版社
ELSEVIER
DOI: 10.1016/j.ssci.2011.04.019
关键词
Data mining; Classification and regression trees (CART); Injury severity; Rural roads
Two-lane, two-way roads constitute a major portion of the rural roads in most countries of the world. This study identifies the factors influencing crash injury severity on these roads in Iran. Classification and regression trees (CART), which is one of the most common methods of data mining, was employed to analyze the traffic crash data of the main two-lane, two-way rural roads of Iran over a 3-year period (2006-2008). In the analysis procedure, the problem of three-class prediction was decomposed into a set of binary prediction models, which resulted in a higher overall accuracy of the predictions of the model. In addition, the prediction accuracy of the fatality class, which was nearly 0% in some of the previous studies, increased significantly. The results indicated that improper overtaking and not using a seatbelt are the most important factors affecting the severity of injuries. (C) 2011 Elsevier Ltd. All rights reserved.
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