Abstract
The use of Kalman filtering techniques in traffic control problems has a long tradition. Based on a macroscopic traffic model, the aim is to extract the actual state of the traffic on a particular road section from a given set of real measurements. Technical developments in the field of traffic telematics make new kinds of information available, like for example, the transmission of velocity profiles from single vehicles (Floating-Car-Data). The unpredictable availability of this additional data leads to a variable structure of the measurement data and, therefore, to switching system dynamics. This contribution examines the stability and convergence properties of traffic state estimation with Floating-Car-Data.
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