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School zone safety modeling in countermeasure evaluation and decision

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dc.contributor.authorPark, Juneyoung-
dc.contributor.authorAbdel-Aty, Mohamed-
dc.contributor.authorLee, Jaeyoung-
dc.date.accessioned2021-06-22T10:26:26Z-
dc.date.available2021-06-22T10:26:26Z-
dc.date.created2021-01-21-
dc.date.issued2019-01-02-
dc.identifier.issn2324-9935-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/3590-
dc.description.abstractSafety of school zone areas has been an important topic in the transportation field because the school zones might cause a risk for the school-aged pedestrians and bicyclists, and motorists due to many types of travel activities near schools. This paper assessed the safety effects of roadway features in school zone areas by exploring the performance of five different types of alternative crash prediction models. The results indicated that the random effects Poisson inverse Gaussian (REPIG) models provide the most accurate crash predictions. Moreover, the results showed that increasing shoulder and lane widths, installation of flashing beacon at school zone speed limit sign, and decreasing the number of driveways were safety effective in reducing crash frequency at school zone areas. The findings from this study offer transportation practitioners and policymakers a dependable reference to enhance safety in schools based on the empirical evidence.-
dc.language영어-
dc.language.isoen-
dc.publisherTAYLOR & FRANCIS LTD-
dc.subjectCRASH MODIFICATION FACTORS-
dc.subjectTRAFFIC ACCIDENT OCCURRENCE-
dc.subjectMOTOR-VEHICLE-
dc.subjectBEFORE-AFTER-
dc.subjectWORK ZONES-
dc.subjectPOISSON-
dc.subjectFREQUENCY-
dc.subjectWIDTH-
dc.subjectSEGMENTS-
dc.subjectLANE-
dc.titleSchool zone safety modeling in countermeasure evaluation and decision-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Juneyoung-
dc.identifier.doi10.1080/23249935.2018.1519646-
dc.identifier.scopusid2-s2.0-85053435395-
dc.identifier.wosid000466728100001-
dc.identifier.bibliographicCitationTRANSPORTMETRICA A-TRANSPORT SCIENCE, v.15, no.2, pp.586 - 601-
dc.relation.isPartOfTRANSPORTMETRICA A-TRANSPORT SCIENCE-
dc.citation.titleTRANSPORTMETRICA A-TRANSPORT SCIENCE-
dc.citation.volume15-
dc.citation.number2-
dc.citation.startPage586-
dc.citation.endPage601-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaTransportation-
dc.relation.journalWebOfScienceCategoryTransportation-
dc.relation.journalWebOfScienceCategoryTransportation Science & Technology-
dc.subject.keywordPlusCRASH MODIFICATION FACTORS-
dc.subject.keywordPlusTRAFFIC ACCIDENT OCCURRENCE-
dc.subject.keywordPlusMOTOR-VEHICLE-
dc.subject.keywordPlusBEFORE-AFTER-
dc.subject.keywordPlusWORK ZONES-
dc.subject.keywordPlusPOISSON-
dc.subject.keywordPlusFREQUENCY-
dc.subject.keywordPlusWIDTH-
dc.subject.keywordPlusSEGMENTS-
dc.subject.keywordPlusLANE-
dc.subject.keywordAuthorTraffic safety-
dc.subject.keywordAuthorschool zone-
dc.subject.keywordAuthormotorized and non-motorized crashes-
dc.subject.keywordAuthorrandom effects Poisson inverse Gaussian-
dc.subject.keywordAuthorcross-sectional method-
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ERICA 공학대학 (DEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING)
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