Fuzzy Observer for State Estimation of the METANET Traffic Model
Traffic control has proven an effective measure to reduce traffic congestion on freeways. In order to determine appropriate control actions, it is necessary to have information on the current state of the traffic. However, not all traffic states can be measured (such as the traffic density) and so state estimation must be applied in order to obtain state information from the available measurements. Linear state estimation methods are not directly applicable, as traffic models are in general nonlinear. In this paper we propose a nonlinear approach to state estimation that is based on a Takagi-Sugeno (TS) fuzzy model representation of the METANET traffic model. By representing the METANET traffic model as a TS fuzzy system, a structured observer design procedure can be applied, whereby the convergence of the observer is guaranteed. Simulation results are presented to illustrate the quality of the estimate.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9781424476572
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Authors:
- Hidayat, Z
- Lendek, Z
- Babuska, R
- De Schutter, B
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Conference:
- 13th International IEEE Conference on Intelligent Transportation Systems (ITSC 2010)
- Location: Madeira Island , Portugal
- Date: 2015-9-19 to 2015-9-22
- Publication Date: 2010
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 19-24
Subject/Index Terms
- TRT Terms: Fuzzy systems; Traffic congestion; Traffic control; Traffic models; Traffic simulation
- Identifier Terms: METANET (Computer program)
- Subject Areas: Highways; Operations and Traffic Management; I70: Traffic and Transport; I71: Traffic Theory;
Filing Info
- Accession Number: 01340601
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- ISBN: 9781424476572
- Files: TLIB
- Created Date: May 20 2011 7:09AM