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    Estimation and Control of Networked Distributed Parameter Systems: Application to Traffic Flow

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    Final Dissertation_Edward_Canepa.pdf
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    10.16Mb
    Format:
    PDF
    Description:
    Final Dissertation
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    Type
    Dissertation
    Authors
    Canepa, Edward S. cc
    Advisors
    Claudel, Christian G. cc
    Committee members
    Shamma, Jeff S. cc
    Parsani, Matteo cc
    Rosales, Rodolfo Rubén
    Program
    Electrical Engineering
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2016-11
    Embargo End Date
    2017-12-06
    Permanent link to this record
    http://hdl.handle.net/10754/621932
    
    Metadata
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    Access Restrictions
    At the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation became available to the public after the expiration of the embargo on 2017-12-06.
    Abstract
    The management of large-scale transportation infrastructure is becoming a very complex task for the urban areas of this century which are covering bigger geographic spaces and facing the inclusion of connected and self-controlled vehicles. This new system paradigm can leverage many forms of sensing and interaction, including a high-scale mobile sensing approach. To obtain a high penetration sensing system on urban areas more practical and scalable platforms are needed, combined with estimation algorithms suitable to the computational capabilities of these platforms. The purpose of this work was to develop a transportation framework that is able to handle different kinds of sensing data (e.g., connected vehicles, loop detectors) and optimize the traffic state on a defined traffic network. The framework estimates the traffic on road networks modeled by a family of Lighthill-Whitham-Richards equations. Based on an equivalent formulation of the problem using a Hamilton-Jacobi equation and using a semi-analytic formula, I will show that the model constraints resulting from the Hamilton-Jacobi equation are linear, albeit with unknown integer variables. This general framework solve exactly a variety of problems arising in transportation networks: traffic estimation, traffic control (including robust control), cybersecurity and sensor fault detection, or privacy analysis of users in probe-based traffic monitoring systems. This framework is very flexible, fast, and yields exact results. The recent advances in sensors (GPS, inertial measurement units) and microprocessors enable the development low-cost dedicated devices for traffic sensing in cities, 5 which are highly scalable, providing a feasible solution to cover large urban areas. However, one of the main problems to address is the privacy of the users of the transportation system, the framework presented here is a viable option to guarantee the privacy of the users by design.
    Citation
    Canepa, E. S. (2016). Estimation and Control of Networked Distributed Parameter Systems: Application to Traffic Flow. KAUST Research Repository. https://doi.org/10.25781/KAUST-82H0A
    DOI
    10.25781/KAUST-82H0A
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-82H0A
    Scopus Count
    Collections
    Dissertations; Dissertations; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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