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dc.contributor.authorKennedy, Jason Forresten
dc.date.accessioned2014-03-14T20:50:26Zen
dc.date.available2014-03-14T20:50:26Zen
dc.date.issued2008-12-10en
dc.identifier.otheretd-12192008-163243en
dc.identifier.urihttp://hdl.handle.net/10919/36308en
dc.description.abstractCrash prediction models are used to estimate the number of crashes using a set of explanatory variables. The highway safety community has used modeling techniques to predict vehicle-to-vehicle crashes for decades. Specifically, generalized linear models (GLMs) are commonly used because they can model non-linear count data such as motor vehicle crashes. Regression models such as the Poisson, Zero-inflated Poisson (ZIP), and the Negative Binomial are commonly used to model crashes. Until recently very little research has been conducted on crash prediction modeling for pedestrian-motor vehicle crashes. This thesis considers several candidate crash prediction models using a variety of explanatory variables and regression functions. The goal of this thesis is to develop a pedestrian crash prediction model to contribute to the field of pedestrian safety prediction research. Additionally, the thesis contributes to the work done by the Federal Highway Administration to estimate pedestrian exposure in urban areas. The results of the crash prediction analyses indicate the pedestrian-vehicle crash model is similar to models from previous work. An analysis of two pedestrian volume estimation methods indicates that using a scaling technique will produce volume estimates highly correlated to observed volumes. The ratio of crash and exposure estimates gives a crash rate estimation that is useful for traffic engineers and transportation policy makers to evaluate pedestrian safety at signalized intersections in an urban environment.en
dc.publisherVirginia Techen
dc.relation.haspartThesis_Kennedy_Jan72009.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCrash modelingen
dc.subjectExposure to risken
dc.subjectSignalized intersectionsen
dc.subjectCrash risk estimationen
dc.subjectPedestrian crashesen
dc.titleEstimating Pedestrian Crashes at Urban Signalized Intersectionsen
dc.typeThesisen
dc.contributor.departmentCivil Engineeringen
dc.description.degreeMaster of Scienceen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineCivil Engineeringen
dc.contributor.committeechairRakha, Hesham A.en
dc.contributor.committeememberHancock, Kathleen L.en
dc.contributor.committeememberMurray-Tuite, Pamela M.en
dc.contributor.committeememberKikuchi, Shinyaen
dc.contributor.committeememberInge, Patches Johnsonen
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12192008-163243/en
dc.date.sdate2008-12-19en
dc.date.rdate2009-01-07en
dc.date.adate2009-01-07en


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