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http://dx.doi.org/10.7470/jkst.2013.31.6.053

Comparison of Methodologies for Characterizing Pedestrian-Vehicle Collisions  

Choi, Saerona (Department of Transportation and Logistics Engineering, Hanyang University)
Jeong, Eunbi (Department of Transportation and Logistics Engineering, Hanyang University)
Oh, Cheol (Department of Transportation and Logistics Engineering, Hanyang University)
Publication Information
Journal of Korean Society of Transportation / v.31, no.6, 2013 , pp. 53-66 More about this Journal
Abstract
The major purpose of this study is to evaluate methodologies to predict the injury severity of pedestrian-vehicle collisions. Methodologies to be evaluated and compared in this study include Binary Logistic Regression(BLR), Ordered Probit Model(OPM), Support Vector Machine(SVM) and Decision Tree(DT) method. Valuable insights into applying methodologies to analyze the characteristics of pedestrian injury severity are derived. For the purpose of identifying causal factors affecting the injury severity, statistical approaches such as BLR and OPM are recommended. On the other hand, to achieve better prediction performance, heuristic approaches such as SVM and DT are recommended. It is expected that the outcome of this study would be useful in developing various countermeasures for enhancing pedestrian safety.
Keywords
binary logistic regression; decision tree; ordered probit model; pedestrian-vehicle accident; support vector machine;
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Times Cited By KSCI : 11  (Citation Analysis)
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