Travel Time Prediction Based on Fuzzy Clustering Method.

Author(s)
Sun, Y. & Honghai, L.
Year
Abstract

This paper discusses a new method based on fuzzy logic that is useful in dealing real world problems. It discusses the build up of a fuzzy clustering system for travel time prediction, proposes utilizing adaptive fuzzy inference model, which will show the results of using the models carried on an application in the Beijing 2nd Ring Road (North-east part). The data consist of real VD data in the pilot area and this is to refine and mining to be used in the model, by implementing approaches during the update procedure. Finally, this paper evaluates the results of the model with real travel time data got by license-plate recognition camera. At last summarize our conclusions.

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Publication

Library number
C 46701 (In: C 46669 CD-ROM) /72 /71 / ITRD E852389
Source

In: ITS in daily life : proceedings of the 16th World Congress on Intelligent Transport Systems (ITS), Stockholm, Sweden, September 21-25, 2009, 8 p.

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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.