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    A sensor network architecture for urban traffic state estimation with mixed eulerian/lagrangian sensing based on distributed computing

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    Type
    Conference Paper
    Authors
    Canepa, Edward S. cc
    Odat, Enas M. cc
    Dehwah, Ahmad H. cc
    Mousa, Mustafa cc
    Jiang, Jiming
    Claudel, Christian G. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Computer Science Program
    Distributed Sensing Systems Laboratory (DSS)
    Date
    2014-02-17
    Online Publication Date
    2014-02-17
    Print Publication Date
    2014
    Permanent link to this record
    http://hdl.handle.net/10754/564873
    
    Metadata
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    Abstract
    This article describes a new approach to urban traffic flow sensing using decentralized traffic state estimation. Traffic sensor data is generated both by fixed traffic flow sensor nodes and by probe vehicles equipped with a short range transceiver. The data generated by these sensors is sent to a local coordinator node, that poses the problem of estimating the local state of traffic as a mixed integer linear program (MILP). The resulting optimization program is then solved by the nodes in a distributed manner, using branch-and-bound methods. An optimal amount of noise is then added to the maps before dissemination to a central database. Unlike existing probe-based traffic monitoring systems, this system does not transmit user generated location tracks nor any user presence information to a centralized server, effectively preventing privacy attacks. A simulation of the system performance on computer-generated traffic data shows that the system can be implemented with currently available technology. © 2014 Springer International Publishing Switzerland.
    Publisher
    Springer Nature
    Journal
    Architecture of Computing Systems – ARCS 2014
    Conference/Event name
    27th International Conference on Architecture of Computing Systems, ARCS 2014
    ISBN
    9783319048901
    DOI
    10.1007/978-3-319-04891-8_13
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-319-04891-8_13
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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