A structural state space model for real-time traffic origin-destination demand estimation and prediction in a day-to-day learning framework
- Author
- XUESONG ZHOU1 ; MAHMASSANI, Hani S2
[1] Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT 84112, United States
[2] Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742, United States - Source
Transportation research. Part B : methodological. 2007, Vol 41, Num 8, pp 823-840, 18 p ; ref : 3/4 p
- CODEN
- TRBMDY
- ISSN
- 0191-2615
- Scientific domain
- Transportation
- Publisher
- Elsevier, Kidlington
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Dynamic OD estimation and prediction Kalman filter Real-time traffic estimation and prediction Traffic system management
- Keyword (fr)
- Affectation trafic Application Apprentissage Filtre Kalman Gestion trafic Modèle origine destination Modèle prévision Modèle structure Système intelligent Temps réel Variation d'un jour à l'autre
- Keyword (en)
- Traffic assignment Application Learning Kalman filter Traffic management Origin destination model Forecast model Structural model Intelligent system Real time Day to day variation
- Keyword (es)
- Afectación tráfico Aplicación Aprendizaje Filtro Kalman Gestión tráfico Modelo origen destinación Modelo previsión Modelo estructura Sistema inteligente Tiempo real Variación de una día al otro
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D15 Ground, air and sea transportation, marine construction / 001D15C Road transportation and traffic
- Discipline
- Building. Public works. Transport. Civil engineering
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 18980948
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.trb.2007.02.004 
https://dx.doi.org/10.1016/j.trb.2007.02.004
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