On the Short-term Prediction of Traffic State: An Application on Urban Freeways in ROME
This paper explores the traffic state estimation on freeways in urban areas combining point-based and route-based data in order to properly feed a second order traffic flow model, recursively corrected by an Extended Kalman Filter. In order to overcome the possible lack of real-time information, the authors propose to use simulation-based data in order to improve the accuracy of the traffic state estimation. This model was tested on an urban freeway stretch in Rome, for which a set of real-time data during the morning of a typical workday was available. Results of the application point out the benefits of the proposed approach in predicting the traffic state, as shown by GEH, RMSE and RME values similar to those presented in the literature.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
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Supplemental Notes:
- © 2015 L. Mannini et al. Published by Elsevier B.V.
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Authors:
- Mannini, L
- Carrese, S
- Cipriani, E
- Crisalli, U
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Conference:
- 18th Euro Working Group on Transportation, EWGT 2015
- Location: Delft , Netherlands
- Date: 2015-7-14 to 2015-7-16
- Publication Date: 2015
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 176-185
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Serial:
- Transportation Research Procedia
- Volume: 10
- Publisher: Elsevier
- ISSN: 2352-1465
- Serial URL: http://www.sciencedirect.com/science/journal/23521465/
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Freeways; Kalman filtering; Traffic flow; Traffic models; Urban areas
- Uncontrolled Terms: Traffic state estimation
- Geographic Terms: Rome (Italy)
- Subject Areas: Highways; Operations and Traffic Management; I71: Traffic Theory;
Filing Info
- Accession Number: 01577952
- Record Type: Publication
- Files: TRIS
- Created Date: Sep 29 2015 8:33AM