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Estimation of Freeway Accident Likelihood using Real-time Traffic Data  

Park, Joon-Hyung (한양대학교 교통시스템공학과)
Oh, Cheol (한양대학교 교통시스템공학과)
NamKoong, Seong (한국도로공사 도로교통기술원)
Publication Information
Journal of Korean Society of Transportation / v.26, no.2, 2008 , pp. 157-166 More about this Journal
Abstract
This study proposed a model to estimate traffic accident likelihood using real-time traffic data obtained from freeway traffic surveillance systems. Traffic variables representing spatio-temporal variations of traffic conditions were utilized as independent variables in the proposed models. Binary logistics regression modelings were conducted to correlate traffic variables and accident data that were collected from the Seohaean freeway during recent three years, from 2004 to 2006. To apply more reliable traffic variables, outlier filtering and data imputation were also performed. The outcomes of the model that are actually probabilistic measures of accident occurrence would be effectively utilized not only in designing warning information systems but also in evaluating the effectiveness of various traffic operations strategies in terms of traffic safety.
Keywords
Traffic safety; Binary Logistic Regression; Warning information; Loop Detector; Accident Likelihood;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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