Evaluation results of the models for monitoring the current and expected traffic state. DRIVE II Project V2044 General European Road Data Information Exchange Network GERDIEN, Deliverable 16, Workpackage SP6.WP3 + Technical Annex 1 + Technical Annex ...

Author(s)
Arem, B. van Vlist, M.J.M. van der Ruiter, J.C.C. de Muste, M. Smulders, S.A. Dougherty, M.S. Cobbett, M.R. & Kirby, H.R.
Year
Abstract

This report aims to validate road section monitoring algorithms. These algorithms are implemented in the DRIVE II General European Road Data Information Exchange Network (GERDIEN) project. The estimates produced by these algorithms have been evaluated, and compared with the Dutch motorway field observation study data. The three submodels implemented are models: (1) for estimating current roadway capacity; (2) for detecting congestion and for estimating travel times; and (3) for predicting the near future traffic state. The results for the models for estimating both the current capacity and travel times were promising. The use of neural networks for forecasting traffic is still at a research stage. The report also includes two technical annexes. See also IRRD 867590 (= C 2980).

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Publication

Library number
C 2982 [electronic version only] /71 /72 / IRRD 867592
Source

Delft, Netherlands Organization for Applied Scientific Research TNO, INRO Centre for Infrastructure, Transport and Regional Development, 1994, 34 + 102 p., 25 ref.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.