• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.106-118
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• 2014

The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.9-15
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• 2011

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.