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

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 counte...

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Bibliographic Details
Published in:International journal of automotive technology 2008, 9(2), , pp.191-196
Main Authors: Oh, C., Kang, Y. S., Youn, Y., Konosu, A.
Format: Article
Language:English
Subjects:
Automobile safety
Automotive Engineering
Dependent variables
Engineering
Fatalities
Independent variables
Neural networks
Pedestrians
Regression analysis
Studies
Traffic accidents & safety
Variables
자동차공학
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Summary: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.
ISSN:1229-9138
1976-3832
DOI:10.1007/s12239-008-0024-7