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dc.contributor.advisorP. Christopher Zegras.en_US
dc.contributor.authorCheng, Phil Tinnen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Urban Studies and Planning.en_US
dc.date.accessioned2016-10-25T19:52:28Z
dc.date.available2016-10-25T19:52:28Z
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/105070
dc.descriptionThesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2016.en_US
dc.description"June 2016." Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 69-72).en_US
dc.description.abstractRapid urbanization and industrialization around the globe have brought urban policymakers complex challenges such as chronic congestion, environmental pollution and socio-economic inequalities. With the rising adoption of and sophistication of social media and personal electronic devices, citizens are increasingly voicing their expectations and hearing those of others from near and afar on what they expect of their city governments. The planning and policymaking of the urban environments and transit systems, due to their complexity and traditional dependence on proprietary tools, have been, by-and-large, a process restricted to those who are deemed as "domain experts". As citizens demand more transparency of, and participation, in the urban planning process, how might policymakers reshape their traditional decision-making processes, to not just align the expectations of diverse interests, but also to make more informed policies by harvesting relevant data from the collective intelligence? This paper documents the creation and evaluation of an interactive, multi-scale, dual-interface transit information system that combined a LEGO-based Tangible User Interface (TUI), Augmented Reality (AR), and cloud computing-based, and interactive data visualizations into a new type of interface aimed at enabling the process of participatory planning. The prototype system used Bus Rapid Transit (BRT) planning in Boston as a pilot case and allowed trial users to see, create, compare and evaluate new transit scenarios. We found potential in the systems to not just convey knowledge related to the chosen topic, but also support social learning and induce change in behavioral intention.en_US
dc.description.statementofresponsibilityby Phil Tinn Cheng.en_US
dc.format.extent72 pagesen_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.titleToward a multi-scale participatory urban policymaking platform : co-designing Mass Transit using LEGO bricks, open data, and interactive pixelsen_US
dc.title.alternativeCo-designing Mass Transit using LEGO bricks, open data, and interactive pixelsen_US
dc.typeThesisen_US
dc.description.degreeM.C.P.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planning
dc.identifier.oclc959838035en_US


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