Fuzzy models and observers for freeway traffic state tracking

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.