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

Edward S. Canepa, Enas M. Odat, Ahmad H. Dehwah, Mustafa Mousa, Jiming Jiang, Christian G. Claudel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

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.
Original languageEnglish (US)
Title of host publicationArchitecture of Computing Systems – ARCS 2014
PublisherSpringer Nature
Pages147-158
Number of pages12
ISBN (Print)9783319048901
DOIs
StatePublished - Feb 17 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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