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- W2381738265 abstract "Appropriate hotspot identification methods can improve the effectiveness of safety management and safety level.Traditional hotspot identification methods(crash frequency method,crash rate method) ignore the influence of traffic characteristic and fluctuation of crash frequencies,which may bring forth biased results.In this study,empirical Bayes method considering potential accident reduction which could resolve the problems of traditional methods was proposed.Based on the dataset of 195 signalized intersections in Shanghai,crash prediction model was developed,using generalized estimating equation(GEE).Safety index of intersections was calculated combined with empirical Bayes and potential accident reduction methods.It was found that,the result of ranking by safety index was significantly different from classical crash frequency method and crash rate method and classical method would result in biased estimations of hotspot." @default.
- W2381738265 created "2016-06-24" @default.
- W2381738265 creator A5065220600 @default.
- W2381738265 date "2011-01-01" @default.
- W2381738265 modified "2023-09-24" @default.
- W2381738265 title "Hotspot Identification of Signalized Intersection Using Empirical Bayes Method" @default.
- W2381738265 hasPublicationYear "2011" @default.
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