Fuzzy Models and Observers for Freeway Traffic State Tracking
Reference
Zs. Lendek,
R. Babuška, 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.
Abstract
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.
Downloads
- Corresponding technical report:
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(333 KB)
Bibtex entry
@inproceedings{LenBab:10-008,
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},
pages={2278--2283},
month=jun # {--} # jul,
year={2010}
}
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Last update: February 21, 2026.