The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions

The identification and ranking of hazardous road locations are important parts of road safety improvement programs. This paper describes the application of Empirical Bayes (EB) approach for identifying and ranking hazardous junctions. Accident, traffic, and junction geometric/environment data from 2...

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Main Authors: Kusumawati, Aine, Wong, Yiik Diew
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2011
Subjects:
Online Access:https://hdl.handle.net/10356/94477
http://hdl.handle.net/10220/7309
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-944772019-12-06T18:56:46Z The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions Kusumawati, Aine Wong, Yiik Diew School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering::Transportation The identification and ranking of hazardous road locations are important parts of road safety improvement programs. This paper describes the application of Empirical Bayes (EB) approach for identifying and ranking hazardous junctions. Accident, traffic, and junction geometric/environment data from 203 four-legged and 186 three-legged signalized junctions across western part of Singapore were collected. Accident prediction models were developed and safety of the junctions was estimated. After that, hazardous junctions were identified using probability of selecting the worst site concept and then ranked using PSI (potential for safety improvement) and LH (level of hazard) criteria. A total of 38 junctions were found as hazardous. The result shows that the use of PSI criterion is more favorable than LH criterion as it is better able to detect the top hazardous junctions with the largest number of accidents in the study period. Published version 2011-11-11T08:21:38Z 2019-12-06T18:56:46Z 2011-11-11T08:21:38Z 2019-12-06T18:56:46Z 2010 2010 Journal Article Kusumawati, A., & Wong, Y. D. (2010). The Application of Empirical Bayes Approach for Identifying and Ranking Hazardous Junctions Case Study: Singapore Signalized Junctions. Journal of the Eastern Asia Society for Transportation Studies, 8, 2062-2077. https://hdl.handle.net/10356/94477 http://hdl.handle.net/10220/7309 en Journal of the Eastern Asia society for transportation studies © 2010 Eastern Asia Society for Transportation Studies. This paper was published in Journal of the Eastern Asia Society for Transportation Studies and is made available as an electronic reprint (preprint) with permission of Eastern Asia Society for Transportation Studies. The paper can be found at the following official URL: [http://www.jstage.jst.go.jp/article/easts/8/0/8_2062/_article].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 16 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Civil engineering::Transportation
spellingShingle DRNTU::Engineering::Civil engineering::Transportation
Kusumawati, Aine
Wong, Yiik Diew
The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
description The identification and ranking of hazardous road locations are important parts of road safety improvement programs. This paper describes the application of Empirical Bayes (EB) approach for identifying and ranking hazardous junctions. Accident, traffic, and junction geometric/environment data from 203 four-legged and 186 three-legged signalized junctions across western part of Singapore were collected. Accident prediction models were developed and safety of the junctions was estimated. After that, hazardous junctions were identified using probability of selecting the worst site concept and then ranked using PSI (potential for safety improvement) and LH (level of hazard) criteria. A total of 38 junctions were found as hazardous. The result shows that the use of PSI criterion is more favorable than LH criterion as it is better able to detect the top hazardous junctions with the largest number of accidents in the study period.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Kusumawati, Aine
Wong, Yiik Diew
format Article
author Kusumawati, Aine
Wong, Yiik Diew
author_sort Kusumawati, Aine
title The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
title_short The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
title_full The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
title_fullStr The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
title_full_unstemmed The application of Empirical Bayes approach for identifying and ranking hazardous junctions case study : Singapore signalized junctions
title_sort application of empirical bayes approach for identifying and ranking hazardous junctions case study : singapore signalized junctions
publishDate 2011
url https://hdl.handle.net/10356/94477
http://hdl.handle.net/10220/7309
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