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Understanding and modeling human movement in cities using phone data

Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016. / S.M. !c Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2016 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 83-88). / Cities today are strained by the exponential growth in population where they are homes to the majority of world's population. Understanding the complexities underlying the emerging behaviors of human travel patterns on the city level is essential toward making informed decision-making pertaining to urban transportation infrastructures This thesis includes several attempts towards modeling and understanding human mobility at the scales of individuals and the scale of aggregate population movement. The second chapter includes the development of a browser delivering visual insights of the aggregate behavior of populations in cities. The third chapter provides a computational framework for clustering regions in cities based on their attraction behavior and in doing so aids a predictive model in predicting inflows to newly developed regions. The fourth chapter investigates the patterns of individuals' movement at the city scale towards developing a predictive model for a persons' next visited location. The predictive accuracy is then increased by adding movement information of the population. The motivation behind the work of this thesis is derived from the demand of tools that provides fine-grained analysis of the complexity of human travel within cites. The approach takes advantage of the existing built infrastructures to sense the mobility of people eliminating the financial and temporal burdens of traditional methods. The outcomes of this work will assist both planners and the public in understanding the complexities of human mobility within their cities. / by Fahad Alhasoun. / S.M. / S.M. !c Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/107058
Date January 2016
CreatorsAlhasoun, Fahad
ContributorsMarta C. González and Una-May O'Reilly., Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science., Massachusetts Institute of Technology. Computation for Design and Optimization Program., Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
PublisherMassachusetts Institute of Technology
Source SetsM.I.T. Theses and Dissertation
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format88 pages, application/pdf
RightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582

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