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dc.contributor.advisorSun, Carloseng
dc.contributor.authorMenneni, Sandeepeng
dc.date.issued2008eng
dc.date.submitted2008 Falleng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on November 12, 2010).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionDissertation advisor: Dr. Carlos Sun.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2008.eng
dc.description.abstractEven though calibration techniques for traffic simulation abound, this dissertation presents the first mathematical formalization using representations and invariants. The calibration is defined succinctly over three levels of representation: traffic, dissimilarity, and search. The methodology encompasses the currently used calibration procedures while improving the calibration process. The theoretical formulation of calibration lays the foundation for several improvements in calibration such as improvement in traffic relationships employed in calibration, new pattern recognition methods for accurate measurement of the differences in complex relationships, and seamless integration into direct search methods. These new methods are demonstrated in the microsimulation of a freeway network in California. In the first case study, speed-flow graphs were shown to replicate field data better than methods based on either capacity or sustained flow. The study also demonstrates the usefulness of pattern recognition in automatically measuring the degree-of-closeness of traffic relationships based on graphs. In the second case study, the calibration process is improved by integrating a microscopic traffic representation (action points) and a macroscopic representation (speed-flow graphs). The microscopic traffic representations are developed by analyzing several leader-follower vehicle pairs from real-world vehicle trajectories.eng
dc.description.bibrefIncludes bibliographical references (p. 147-150).eng
dc.format.extent158 pageseng
dc.identifier.oclc681912288eng
dc.identifier.urihttps://hdl.handle.net/10355/9102
dc.identifier.urihttps://doi.org/10.32469/10355/9102eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subject.lcshTraffic engineering -- Simulation methodseng
dc.subject.lcshTraffic patterns -- Simulation methodseng
dc.subject.lcshTraffic engineering -- Mathematical modelseng
dc.subject.lcshTraffic patterns -- Mathematical modelseng
dc.subject.lcshPattern recognition systemseng
dc.titlePattern recognition based microsimulation calibration and innovative traffic representationseng
dc.typeThesiseng
thesis.degree.disciplineCivil engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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