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Time series trends of the safety effects of pavement resurfacing

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dc.contributor.authorPark, Juneyoung-
dc.contributor.authorAbdel-Aty, Mohamed-
dc.contributor.authorWang, Jung-Han-
dc.date.accessioned2021-06-22T14:23:10Z-
dc.date.available2021-06-22T14:23:10Z-
dc.date.created2021-01-21-
dc.date.issued2017-04-
dc.identifier.issn0001-4575-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/10070-
dc.description.abstractThis study evaluated the safety performance of pavement resurfacing projects on urban arterials in Florida using the observational before and after approaches. The safety effects of pavement resurfacing were quantified in the crash modification factors (CMFs) and estimated based on different ranges of heavy vehicle traffic volume and time changes for different severity levels. In order to evaluate the variation of CMFs over time, crash modification functions (CMFunctions) were developed using nonlinear regression and time series models. The results showed that pavement resurfacing projects decrease crash frequency and are found to be more safety effective to reduce severe crashes in general. Moreover, the results of the general relationship between the safety effects and time changes indicated that the CMFs increase over time after the resurfacing treatment. It was also found that pavement resurfacing projects for the urban roadways with higher heavy vehicle volume rate are more safety effective than the roadways with lower heavy vehicle volume rate. Based on the exploration and comparison of the developed CMFucntions, the seasonal autoregressive integrated moving average (SARIMA) and exponential functional form of the nonlinear regression models can be utilized to identify the trend of CMFs over time. (C) 2017 Elsevier Ltd. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleTime series trends of the safety effects of pavement resurfacing-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Juneyoung-
dc.identifier.doi10.1016/j.aap.2017.02.006-
dc.identifier.wosid000396974300009-
dc.identifier.bibliographicCitationACCIDENT ANALYSIS AND PREVENTION, v.101, pp.78 - 86-
dc.relation.isPartOfACCIDENT ANALYSIS AND PREVENTION-
dc.citation.titleACCIDENT ANALYSIS AND PREVENTION-
dc.citation.volume101-
dc.citation.startPage78-
dc.citation.endPage86-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaPublic, Environmental & Occupational Health-
dc.relation.journalResearchAreaSocial Sciences - Other Topics-
dc.relation.journalResearchAreaTransportation-
dc.relation.journalWebOfScienceCategoryErgonomics-
dc.relation.journalWebOfScienceCategoryPublic, Environmental & Occupational Health-
dc.relation.journalWebOfScienceCategorySocial Sciences, Interdisciplinary-
dc.relation.journalWebOfScienceCategoryTransportation-
dc.subject.keywordPlusACCIDENT MODIFICATION FUNCTIONS-
dc.subject.keywordPlusCRASH MODIFICATION FUNCTIONS-
dc.subject.keywordPlusINTERVENTION ANALYSIS-
dc.subject.keywordPlusMULTIPLE TREATMENTS-
dc.subject.keywordPlusINJURY-SEVERITY-
dc.subject.keywordPlusROADWAY-
dc.subject.keywordAuthorSafety effects-
dc.subject.keywordAuthorPavement resurfacing-
dc.subject.keywordAuthorCrash modification factors and functions-
dc.subject.keywordAuthorNonlinear models-
dc.subject.keywordAuthorTime series models-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0001457517300568-
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ERICA 공학대학 (DEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING)
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