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dc.contributor.advisorJohn P. Attanucci and Rabi G. Mishalani.en_US
dc.contributor.authorUniman, David Louisen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Urban Studies and Planning.en_US
dc.date.accessioned2010-03-24T20:39:27Z
dc.date.available2010-03-24T20:39:27Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/52806
dc.descriptionThesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2009.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 162-165).en_US
dc.description.abstractService reliability is an important dimension of performance to transit passengers, affecting not only their perceptions of service quality, but their travel behaviour as well. The ability of transit operators to understand and improve reliability relies on their ability to measure it. Until recently, efforts to quantify this attribute of service from the perspective of passengers were limited by the small sample sizes obtained from manual surveys, or the use of supply-side data to indirectly capture the passenger experience. With the emergence of data from automated fare media, it becomes possible under certain conditions to directly observe travel times experienced by passengers and obtain improved estimates of the reliability of transit service. A framework is developed to estimate service reliability on heavy rail transit systems with both entry and exit fare control using data from Automated Fare Collection systems. A methodology is proposed as part of the framework to classify performance into incident-related and recurrent conditions in order to both gain new insight into the contribution of the different causes of unreliability as well as develop more robust measures of service reliability. The classification methodology is validated against incident log data corresponding to three origin-destination (O-D) pairs on the London Underground. Subsequently, the proposed framework is used to characterize the reliability of 800 Underground O-D pairs representing the highest-volume journeys on the system. Furthermore, models are estimated to quantify the effects of journey length, interchanges, and incident-related disruptions on reliability.en_US
dc.description.abstract(cont.) Two practical applications of the framework are also developed for the Underground. First, an extension of the existing service quality measurement system is proposed in order to quantify reliability as part of routine performance monitoring efforts. An application of this extension to the Victoria line during the morning peak reveals that reliability is an important part of service quality, with a contribution to total perceived travel times comparable to that of various average travel time components. Second, a way to provide passengers with reliability information through Transport for London's trip planning software is presented, in order to mitigate the negative impact of uncertain journey times. The potential benefits from the provision of this additional information are found to be appreciable relative to the current ability of the trip planning software to reduce uncertainty for Underground passengers.en_US
dc.description.statementofresponsibilityby David Louis Uniman.en_US
dc.format.extent165 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.subjectUrban Studies and Planning.en_US
dc.titleService reliability measurement framework using smart card data : application to the London Undergrounden_US
dc.typeThesisen_US
dc.description.degreeM.C.P.en_US
dc.description.degreeS.M.in Transportationen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planning
dc.identifier.oclc549498273en_US


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