Development of probabilistic pedestrian fatality model for characterizing pedestrian-vehicle collisions.

Author(s)
Oh, C. Kang, Y.S. Youn, Y. & Konosu, A.
Year
Abstract

Pedestrian-related accidents are considered to be the most serious of traffic accidents due to the associated high fatality rates. In Korea, pedestrian fatalities accounted for approximately 40% of all traffic-related fatalities in 2004. Significant efforts have been made to develop effective countermeasures for pedestrian-vehicle collisions. A basis for devising such countermeasures is to understand the characteristics of pedestrian-vehicle collisions. This study develops a pedestrian fatality model capable of predicting the probability of fatality in pedestrian-vehicle collisions. Binary logistic regression and a probabilistic neural network (PNN) are employed to estimate the probability of pedestrian fatality. Pedestrian age, vehicle type and collision speed are used as independent variables of the fatality model. The models developed herein are valuable tools that can be used to direct safety policies and technologies associated with pedestrian safety. (Author/publisher)

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Publication

Library number
20210624 ST [electronic version only]
Source

International Journal of Automotive Technology, Vol. 9 (2008), No. 2 (April), p. 191-196, 20 ref.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.