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Paper Information

Journal:   JOURNAL OF TRANSPORTATION RESEARCH   SUMMER 2010 , Volume 7 , Number 2 (23); Page(s) 153 To 165.
 
Paper: 

ANALYSIS OF TWO-LANE, TWO-WAY RURAL ROADS TRAFFIC INJURY SEVERITY BASED ON DATA MINING MODELS

 
 
Author(s):  SHARIAT MOHAYMANY A.*, TAVAKOLI KASHANI A.
 
* DEPARTMENT OF CIVIL ENGINEERING, IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY, TEHRAN, IRAN
 
Abstract: 

In this study, factors influencing driver and occupant injury severity in two lane , two way roads of Iran are identified. Using statistical models is one of the most common methods that were employed to analyze crash severity. In this study, in addition to examining such models and expressing their weak points, CART method is introduced. Classification and regression trees (CART), which is one of the most common methods of data mining, was employed to analyze the traffic crash data over a three-year period (2006-2008). Expressing models in decision tree format with explicit rules is one of their most useful outputs. In the analysis procedure, the problem of three-class prediction was decomposed into a set of binary prediction models and then eight models were analyzed. This resulted higher overall accuracy of predicting the model, besides the prediction accuracy of the fatality class, which was nearly 0%, and in most of the previous studies, increased significantly. Results indicated that improper overtaking and ignoring seat belts are the most important factors affecting the severity of injuries.

 
Keyword(s): DATA MINING, CLASSIFICATION AND REGRESSION TREES (CART), INJURY SEVERITY, RURAL ROADS
 
References: 
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