Traffic state estimation using hierarchical clustering and principle components analysis : a practical approach.

Author(s)
Foerster, G.
Year
Abstract

Traffic state estimation and prediction are fundamental requirements for automatic control of urban road traffic with both adaptive traffic lights and variable message signs. For that, collecting of actual traffic data is necessary. This paper deals with the combined application of principle components analysis (PCA) and hierarchical cluster analysis (HCA) for the specification of the needed number of stationary road traffic sensors and their preferable locations within a given road network. Both methods are introduced briefly. A practicable procedure for using these methods is derived and it is shown that their combination is effective. First tests based on microscopic simulation data and on real volumes of inductive. (Author/publisher)

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Publication

Library number
20071561 k ST (In: 20071561 ST CD-ROM)
Source

In: Young Researchers Seminar 2007, Brno, Czech Republic, 27-30 May 2007, arranged by European Conference of Transport Research Institutes ECTRI, Forum of European National Highway Research Laboratories FEHRL, Centrum Dopravniho Vyzkumu and Forum of European Road Safety Research Institutes (FERSI), 12 p., 8 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.