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A multivariate analysis of crash and naturalistic driving data in relation to highway factors

dc.contributor.authorGordon, T. J.en_US
dc.contributor.authorKostyniuk, L. P.en_US
dc.contributor.authorGreen, P. E.en_US
dc.contributor.authorBarnes, M. A.en_US
dc.contributor.authorBlower, D. F.en_US
dc.contributor.authorBogard, S. E.en_US
dc.contributor.authorBlankespoor, A. D.en_US
dc.contributor.authorLeBlanc, D. J.en_US
dc.contributor.authorCannon, B. R.en_US
dc.contributor.authorMcLaughlin, S. B.en_US
dc.date.accessioned2013-08-20T15:36:12Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2013-08-20T15:36:12Z
dc.date.issued2013
dc.identifierAccession Number: 102952en_US
dc.identifier.otherSHRP 2 Report S2-S01C-RW-1en_US
dc.identifier.otherProject Number: S01(C)en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/99551
dc.descriptionAppendices; Figures; References; Tablesen_US
dc.description.abstractThis report documents the second phase of a two-phase project under the Transportation Research Board’s second Strategic Highway Research Program (SHRP 2) Safety Project S01C. A primary part of this work involved conducting a multivariate analysis of crash and naturalistic driving data in relation to highway factors. A geographic information system (GIS) framework was used as the basis for fusing multiple information sources to analyze road departure crash risk. A major goal was to use this method to support formulation and validation of crash surrogates. Two analytical models developed in the study focus on the statistical relationship between surrogate measures of crashes and actual crashes and on the formulation of exposure-based risk measures using surrogate measures. The report also describes three exploratory studies that illustrate the value of the geospatial approach taken. The results of each exploratory study suggest that the combination of naturalistic, crash, and highway data provides a rich data resource for many types of research. This report provides valuable background information to highway safety analysts seeking to use the data that will be made available from the SHRP 2 naturalistic driving study.en_US
dc.format.extent77en_US
dc.languageEnglishen_US
dc.publisherTransportation Research Board, Washington, DCen_US
dc.relation.ispartofseriesSHRP 2 Reporten_US
dc.subject.otherAutomatic Data Collection Systemsen_US
dc.subject.otherCrash Dataen_US
dc.subject.otherCrash Exposureen_US
dc.subject.otherCrash Risk Forecastingen_US
dc.subject.otherData Fusionen_US
dc.subject.otherGeographic Information Systemsen_US
dc.subject.otherHighway Factors in Crashesen_US
dc.subject.otherHighway Safetyen_US
dc.subject.otherMultivariate Analysisen_US
dc.titleA multivariate analysis of crash and naturalistic driving data in relation to highway factorsen_US
dc.typeTechnical Reporten_US
dc.subject.hlbsecondlevelTransportation
dc.subject.hlbtoplevelEngineering
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/99551/1/102952.pdf
dc.owningcollnameTransportation Research Institute (UMTRI)


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