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dc.contributor.advisorZhang, Leien_US
dc.contributor.authorXiong, Chenfengen_US
dc.date.accessioned2012-02-17T07:06:18Z
dc.date.available2012-02-17T07:06:18Z
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1903/12360
dc.description.abstractThis thesis comprehensively studies departure time choice models, and analyzes the consequent system-level peak spreading effects. In modeling, the school of discrete choice models successfully reveals the user heterogeneity. A mixture logit model and a latent class model based on the notion of carpooling preference have been estimated. Then a novel positive approach has been developed, which avoids the assumptions of rationality and focuses on how individuals actually make departure time decisions. Following this positive theory, we specify Bayesian learning, empirically estimate search start and stopping conditions that vary among users, and empirically derive search and decision rules from a joint reveal/stated-preference survey dataset. This innovative behavioral model is integrated with a traffic simulation model for a real-world study. Findings from this application reveal the potential of the proposed model to capture network dynamics and behavioral reactions. This integrated framework also provides a valuable tool for the evaluation of new transportation infrastructures, policies, and operation strategies.en_US
dc.titleALL ABOUT CONGESTION: MODELING DEPARTURE TIME DYNAMICS AND ITS INTEGRATION WITH TRAFFIC MODELSen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentCivil Engineeringen_US
dc.subject.pqcontrolledTransportation planningen_US
dc.subject.pqcontrolledCivil engineeringen_US
dc.subject.pqcontrolledBehavioral sciencesen_US
dc.subject.pquncontrolledDeparture time choiceen_US
dc.subject.pquncontrolledIntegrated modelen_US
dc.subject.pquncontrolledLatent classen_US
dc.subject.pquncontrolledNormative theoryen_US
dc.subject.pquncontrolledPositive theoryen_US
dc.subject.pquncontrolledTraffic simulationen_US


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