A sensor network architecture for urban traffic state estimation with mixed eulerian/lagrangian sensing based on distributed computing
AuthorsCanepa, Edward S.
Odat, Enas M.
Dehwah, Ahmad H.
Claudel, Christian G.
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Computer Science Program
Distributed Sensing Systems Laboratory (DSS)
Online Publication Date2014-02-17
Print Publication Date2014
Permanent link to this recordhttp://hdl.handle.net/10754/564873
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AbstractThis 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.
CitationCanepa, E., Odat, E., Dehwah, A., Mousa, M., Jiang, J., & Claudel, C. (2014). A Sensor Network Architecture for Urban Traffic State Estimation with Mixed Eulerian/Lagrangian Sensing Based on Distributed Computing. Lecture Notes in Computer Science, 147–158. doi:10.1007/978-3-319-04891-8_13
Conference/Event name27th International Conference on Architecture of Computing Systems, ARCS 2014