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Analysis of Factors Affecting Pedestrian Leg Injury Severity  

Park, Jae-Hong (Infrastructure Research Department, Korea Institute of Construction Technology)
Oh, Cheol (Department of Transportation Engineering, Hanyang University)
Publication Information
Transactions of the Korean Society of Automotive Engineers / v.19, no.3, 2011 , pp. 9-15 More about this Journal
Abstract
This study analyzed contributing factors affecting leg injury severity in pedestrian-vehicle crashes. A Binary Logistic Regression (BLR) method was used to identify the factors. Independent variables include characteristics for pedestrian, vehicle, road, and environmental conditions. The leg injury severity is classified into two classes, which are dependent variables in this study, such as 'severe' and 'minor' injuries. Pedestrian age, collision speed, and the height of vehicle were identified as significant factors for the leg injury. The probabilistic outcome of predicting leg injury severity can be effectively used in not only deriving pedestrian-related safety policies but also developing advanced vehicular technologies for pedestrian protection.
Keywords
Binary logistic regression; Pedestrian accident; Pedestrian safety; Leg injury severity;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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