Show simple item record

dc.contributor.advisorFrederick P. Salvucci.en_US
dc.contributor.authorTribone, Dominick (Dominick Anthony)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Civil and Environmental Engineering.en_US
dc.coverage.spatialn-us-maen_US
dc.date.accessioned2013-10-24T17:38:12Z
dc.date.available2013-10-24T17:38:12Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/81640
dc.descriptionThesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning; and, (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2013.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 117-119).en_US
dc.description.abstractAs public transit agencies install new technology systems they are gaining increasing amounts of data. This data has the potential to change how they operate by generating better information for decision-making. Deriving value from this data and applying it to improve service requires changing the institutional processes that developed when agencies had little reliable information about their systems and customers. With automated systems producing large quantities of high quality data, it becomes the impetus for, rather than simply the input to, measurement. Capturing more value from automated data thus involves rethinking what agencies can know about service. This research uses the Massachusetts Bay Transportation Authority (MBTA) as a case study. It first assesses how the MBTA currently uses real-time and historical data. Based on this assessment, it redesigns and advances the agency's daily performance reports for rapid transit through a collaborative and iterative process with the Operations Control Center. These reports are then used to identify poor performance, implement pilot projects to address its causes, and evaluate the effects of these pilots. Through this case study, this research finds that service controllers' trust and interpretation of performance information determines its impact on operations. It concludes that new data will be most effective in producing service improvements if measurements accurately reflect human experience and are developed in conjunction with their eventual users. It also finds that developing pilot projects during this collaborative process enables new performance information to result in service improvements. Based on these findings, this work produces a set of recommendations for generating useful performance information from transit data, as well as a specific set of recommendations for expanding the use of data at the MBTA.en_US
dc.description.statementofresponsibilityby Dominick Tribone.en_US
dc.format.extent130 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.subjectUrban Studies and Planning.en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleMaking data matter : the role of information design and process in applying automated data to improve transit serviceen_US
dc.title.alternativeRole of information design and process in applying automated data to improve transit serviceen_US
dc.typeThesisen_US
dc.description.degreeS.M.in Transportationen_US
dc.description.degreeM.C.P.en_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.oclc859408312en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record