A static model for predicting disrupted network behavior

dc.contributor.advisorWaller, S. Travisen
dc.contributor.committeeMemberLove, Bradley C.en
dc.creatorAlsup, Renee M.en
dc.date.accessioned2010-12-20T22:27:45Zen
dc.date.available2010-12-20T22:27:45Zen
dc.date.available2010-12-20T22:27:49Zen
dc.date.issued2010-08en
dc.date.submittedAugust 2010en
dc.date.updated2010-12-20T22:27:49Zen
dc.descriptiontexten
dc.description.abstractThis thesis compares actual and perceived travel times and presents a model for predicting traffic flows when there is a network disruption. The goal of this research is to demonstrate the necessity of accounting for possible differences in travel time perception and actual travel times, and also to show trends in how the route choices change based on the transformation of the perceived travel times. A pilot test was done to determine actual travel time perceptions, and the results provided the foundation for the tests presented in this thesis and the model framework. The model is separated into three phases: equilibrium assignment, link travel time transform, and logit assignment. The transform of the link travel times is best represented by an inverse cumulative Normal distribution, and the corresponding values provide quantifiable measure of the severity of a traffic network disruption. The methodology is presented and applied to two test networks to demonstrate the resulting route choice patterns. Both networks are tested for three severity levels and three levels of demand.en
dc.description.departmentCivil, Architectural, and Environmental Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-08-1910en
dc.language.isoengen
dc.subjectNetwork disruptionen
dc.subjectPerceived travel time distributionen
dc.subjectTravel time transformen
dc.subjectStochastic network assignmenten
dc.titleA static model for predicting disrupted network behavioren
dc.type.genrethesisen
thesis.degree.departmentCivil, Architectural, and Environmental Engineeringen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen

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