Traffic State Estimation Using Floating Car Data
Increasing availability of floating car data both historic in the form of trajectory data-sets and real-time in the form of continuous data stream paves the way for data driven traffic simulations. While historic data-sets can be used to construct spatiotemporal models of different roads, the continuous data streams from probe vehicles can be used for purposes such as current traffic-state estimation, incident detection and predicting short term evolution of traffic. A service which incorporates the aforementioned features will be invaluable for advanced traffic management and information services. In this paper the authors present a thorough analyses of using probe vehicles for reconstructing traffic state in real time, by employing detailed agent based microscopic traffic simulations of several scenarios on real world expressway.
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- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/18770509
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Supplemental Notes:
- © Abhinav Sunderrajan et al. Published by Elsevier B.V.
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Authors:
- Sunderrajan, Abhinav
- Viswanathan, Vaisagh
- Cai, Wentong
- Knoll, Alois
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Conference:
- International Conference on Computational Science (ICCS 2016)
- Location: San Diego California, United States
- Date: 2016-6-6 to 2016-6-8
- Publication Date: 2016
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: pp 2008-2018
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Serial:
- Procedia Computer Science
- Volume: 80
- Publisher: Elsevier
- ISSN: 1877-0509
- Serial URL: http://www.sciencedirect.com/science/journal/18770509
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Expressways; Floating car data; Real time information; Traffic congestion; Traffic simulation
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01605478
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 27 2016 9:51AM