This talk describes a new architecture for distributed flash flood and traffic monitoring in cities using combined Eulerian and Lagrangian sensing. Unlike current traffic sensor networks, the architecture maintains user privacy by using a distributed computing approach.

In this system, probe vehicles broadcast speed data to local nodes, which estimate vehicles location. Fixed sensors also measure traffic parameters, and all traffic data is forwarded to local coordinator nodes. Using the classical LWR traffic flow model, we show that the traffic reconstruction problem results in a set of MILPs, which can be efficiently solved by all nodes using distributed computing, the coordinator node supervising all computations. With this approach, user privacy is maintained, in the sense that no vehicle track data is forwarded beyond the radio range of the node cluster.

Biography:
Christian Claudel is an assistant professor of Electrical Engineering and Mechanical engineering at KAUST. He received the PhD degree in EECS from UC Berkeley in 2010, and the Ms degree in Plasma Physics from Ecole Normale Superieure de Lyon in 2004. He received the Leon Chua Award from UC Berkeley in 2010 for his work on Mobile Millennium. His research interests include control and estimation of distributed parameter systems, wireless sensor networks and environmental sensing systems

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