Evaluating Transportation Network Mobility and Enhancing Traffic Signal Operations Performance Using Probe Data and Connected Vehicle Technology

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dc.contributorJones, Steven L.
dc.contributorLiu, Jun
dc.contributorAtkison, Travis L.
dc.contributorSmith, Randy K.
dc.contributor.advisorHainen, Alexander M.
dc.contributor.authorTalukder, MD Abu Sufian
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2021-11-23T14:34:01Z
dc.date.available2021-11-23T14:34:01Z
dc.date.issued2021
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractHigh-quality, reliable, and robust data is key to better understanding performance and improvement needs for transportation infrastructure. Predominantly, transportation systems performance has been evaluated using infrastructure-based data, which is often limited by high costs, small sample size, and potential inaccuracy. With recent advancements in technology, previously unobtainable large high-fidelity data, such as probe data and connected vehicle (CV) data, can now be utilized to address many challenges related to transportation systems. This dissertation investigates various research and practical oriented applications for such emerging transportation data sources. The first part of this dissertation develops a novel methodology for characterizing mobility of transportation networks. Using probe vehicle travel times, a route-based travel time reliability metric is proposed for assessing and comparing transportation system’s performance from one geographic area to another. The second part of this dissertation uses CV-technology to develop methodology for improving operational efficiency at a signalized intersection. Two innovative traffic signal control algorithms are established to demonstrate real-time delay optimization for both connected and non-connected vehicles. The third part of this dissertation extends the use of CV-technology to facilitate prioritized freight movement in a signalized corridor. An estimated time of arrival (ETA)-based priority logic is developed, and the proposed priority system is deployed along US-82 in Northport and Tuscaloosa, Alabama. Finally, this dissertation explores the application of emerging transportation data collection technologies to characterize and evaluate transportation systems performance. The techniques presented in this dissertation will be helpful to transportation agencies, planners, and practitioners to assess existing performance and need for future transportation infrastructure.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otherhttp://purl.lib.ua.edu/181477
dc.identifier.otheru0015_0000001_0003916
dc.identifier.otherTalukder_alatus_0004D_14565
dc.identifier.urihttp://ir.ua.edu/handle/123456789/8148
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectConnected Vehicle
dc.subjectFreight Signal Priority
dc.subjectMobility
dc.subjectProbe data
dc.subjectTraffic Signal Control
dc.titleEvaluating Transportation Network Mobility and Enhancing Traffic Signal Operations Performance Using Probe Data and Connected Vehicle Technologyen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Civil, Construction, and Environmental Engineering
etdms.degree.disciplineCivil engineering
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.
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