Estimation of Mixed Distributions on Vehicular Traffic Measurements using the Bluetooth Technology

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dc.contributor.advisorLa, Richarden_US
dc.contributor.authorZoto, Jorgosen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2012-07-06T11:26:58Z
dc.date.available2012-07-06T11:26:58Z
dc.date.issued2012en_US
dc.description.abstractIn this work we build on the idea of using Bluetooth® sensors as a new intelligent transportation system application of estimating travel time along a section of a highway. Given the existence of High Occupancy Vehicle (HOV) lanes and Express lanes in the U.S highway network, a mixed population estimation problem naturally arises. This estimation problem is attacked from three dierent perspectives: (i) in light of the Expectation Maximization (EM) algorithm, (ii) using Maximum Likelihood Estimation (MLE) techniques and nally (iii) applying a cluster-separation approach to our mixed dataset. The robust performance of the rst approach leads to an EM-inspired MLE technique, a hybrid of (i) and (ii) which combines the good estimation accuracy of EM based algorithms and the lower complexity of MLE techniques. The limitations and performance of all four approaches are tested on actual vehicular data on different highway segments in two dierent U.S states. The superiority of the hybrid approach is shown along with it's limitations.en_US
dc.identifier.urihttp://hdl.handle.net/1903/12560
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pquncontrolledBluetooth devicesen_US
dc.subject.pquncontrolledExpectation Maximizationen_US
dc.subject.pquncontrolledMaximum Likelihooden_US
dc.titleEstimation of Mixed Distributions on Vehicular Traffic Measurements using the Bluetooth Technologyen_US
dc.typeThesisen_US

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