Fuzzy models and observers for freeway traffic state tracking

Zs. Lendek, R. Babuska, and B. De Schutter, "Fuzzy models and observers for freeway traffic state tracking," Proceedings of the 2010 American Control Conference, Baltimore, Maryland, pp. 2278-2283, June-July 2010.

Traffic state estimation is a prerequisite for traffic surveillance and control. For macroscopic traffic flow models several estimation methods have been investigated, including extended and unscented Kalman filters and particle filters. In this paper we propose a fuzzy observer for the continuous time version of the macroscopic traffic flow model METANET. In order to design the observer, we first derive a dynamic Takagi-Sugeno fuzzy model that exactly represents the traffic model of a segment of a highway stretch. The fuzzy observer is designed based on the fuzzy model and applied to the traffic model. The simulation results are promising for the future development of fuzzy observers for a highway stretch or a whole traffic network.

 * Corresponding technical report: pdf file (172 KB)
      Note: More information on the pdf file format mentioned above can be found here.

Bibtex entry:

        author={{\relax Zs}. Lendek and R. Babu{\v{s}}ka and B. {D}e Schutter},
        title={Fuzzy models and observers for freeway traffic state tracking},
        booktitle={Proceedings of the 2010 American Control Conference},
        address={Baltimore, Maryland},
        month=jun # {--} # jul,

Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: December 15, 2015.