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Incorporating Automated Vehicle Identification Data into Origin-Destination Estimation
MIT.
Northeastern University, 437 Snell Engineering Center.
2004 (English)In: TRANSPORTATION NETWORK MODELING 2004, Istanbul, Turkey, 2004, 37-44 p.Conference paper, Published paper (Refereed)
Abstract [en]

A methodology for the incorporation of automated vehicle identification (AVI) data into origin-destination (O-D) estimation and prediction is presented. AVI technologies facilitate the collection of useful data, such as point-to-point travel times and subpath flows. A framework for the incorporation of AVI data into the well-established O-D estimation and prediction process is presented. Improvements are proposed for both the formulation and the inputs to the O-D estimation and prediction model. Furthermore, as the O-D estimation and prediction process is often used in the traffic estimation and prediction context, approaches to the incorporation of AVI data into other areas of the dynamic traffic assignment framework are outlined. Performance and computational issues are also considered, and the results of a case study are presented to demonstrate the approach.

Place, publisher, year, edition, pages
Istanbul, Turkey, 2004. 37-44 p.
Series
Transportation research record-series, ISSN 0361-1981
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-115937ISI: 000227334100005Scopus ID: 2-s2.0-14044268745OAI: oai:DiVA.org:kth-115937DiVA: diva2:588518
Conference
83rd Annual Meeting of the Transportation-Research-Board
Note

TSC import 2008 2013-01-15 QC 20130627

Available from: 2013-01-15 Created: 2013-01-15 Last updated: 2014-04-03Bibliographically approved

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CiteExportLink to record
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  • apa
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Language
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  • Other locale
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Output format
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