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dc.contributor.advisorWu, Yao-Janen
dc.contributor.authorCooke, Payton
dc.creatorCooke, Paytonen
dc.date.accessioned2017-03-23T21:57:01Z
dc.date.available2017-03-23T21:57:01Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10150/622847
dc.description.abstractArterial performance measurement is an essential tool for both researchers and practitioners, guiding decisions on traffic management, future improvements, and public information. Link travel time and intersection control delay are two primary performance measures that are used to evaluate arterial level of service. Despite recent technological advancements, collecting travel time and intersection delay data can be a time-consuming and complicated process. Limited budgets, numerous available technologies, a rapidly changing field, and other challenges make performance measurement and comparison of data sources difficult. Three common data collection sources (probe vehicles, Bluetooth media access control readers, and manual queue length counts) are often used for performance measurement and validation of new data methods. Comparing these and other data sources is important as agencies and researchers collect arterial performance data. This study provides a methodology for comparing data sources, using statistical tests and linear correlation to compare methods and identify strengths and weaknesses. Additionally, this study examines data normality as an issue that is seldom considered, yet can affect the performance of statistical tests. These comparisons can provide insight into the selection of a particular data source for use in the field or for research. Data collected along Grant Road in Tucson, Arizona, was used as a case study to evaluate the methodology and the data sources. For evaluating travel time, GPS probe vehicle and Bluetooth sources produced similar results. Bluetooth can provide a greater volume of data more easily in addition to samples large enough for more rigorous statistical evaluation, but probe vehicles are more versatile and provide higher resolution data. For evaluating intersection delay, probe vehicle and queue count methods did not always produce similar results.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectControl Delayen
dc.subjectProbe Vehicleen
dc.subjectQueue Counten
dc.subjectTravel Timeen
dc.subjectBluetoothen
dc.titleComparative Analysis of Multiple Data Sources for Travel Time and Delay Measurementen_US
dc.typetexten
dc.typeElectronic Thesisen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.levelmastersen
dc.contributor.committeememberWu, Yao-Janen
dc.contributor.committeememberChiu, Yi Changen
dc.contributor.committeememberAtler, David M.en
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineCivil Engineering and Engineering Mechanicsen
thesis.degree.nameM.S.en
refterms.dateFOA2018-08-14T23:39:58Z
html.description.abstractArterial performance measurement is an essential tool for both researchers and practitioners, guiding decisions on traffic management, future improvements, and public information. Link travel time and intersection control delay are two primary performance measures that are used to evaluate arterial level of service. Despite recent technological advancements, collecting travel time and intersection delay data can be a time-consuming and complicated process. Limited budgets, numerous available technologies, a rapidly changing field, and other challenges make performance measurement and comparison of data sources difficult. Three common data collection sources (probe vehicles, Bluetooth media access control readers, and manual queue length counts) are often used for performance measurement and validation of new data methods. Comparing these and other data sources is important as agencies and researchers collect arterial performance data. This study provides a methodology for comparing data sources, using statistical tests and linear correlation to compare methods and identify strengths and weaknesses. Additionally, this study examines data normality as an issue that is seldom considered, yet can affect the performance of statistical tests. These comparisons can provide insight into the selection of a particular data source for use in the field or for research. Data collected along Grant Road in Tucson, Arizona, was used as a case study to evaluate the methodology and the data sources. For evaluating travel time, GPS probe vehicle and Bluetooth sources produced similar results. Bluetooth can provide a greater volume of data more easily in addition to samples large enough for more rigorous statistical evaluation, but probe vehicles are more versatile and provide higher resolution data. For evaluating intersection delay, probe vehicle and queue count methods did not always produce similar results.


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