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A Neural Network Approach for Motorway OD Matrix Estimation from Loop Counts

Mussone, L, Grant-Muller, S and Chen, H (2010) A Neural Network Approach for Motorway OD Matrix Estimation from Loop Counts. Journal of Transportation systems Engineering and Information Technology, 10 (1). 88 - 98 . ISSN 1570-6672


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A method has been developed to estimate Origin Destination (OD) matrices using a neural network (NN) model and loop traffic data collected from a UK motorway site (M42) as the primary input. The estimated ODs were validated against matched vehicle number plate data derived from the ANPR (Automatic Number Plate Recognition) cameras which were installed at all the slip roads between junctions 3a and 7 of the motorway. Key research questions were: whether it is realistic to use the full loop data, whether particular features of the data influenced modelling success, whether data transformation could improve modelling performance through variance stabilization and whether individual ODs should be estimated separately or simultaneously. The method has been shown to work well and the best results were obtained using a square root transformation of the training data and individual models for each OD.

Item Type: Article
Copyright, Publisher and Additional Information: © 2010 Elsevier B.V. This is an author produced version of a paper subsequently published in Journal of Transportation systems Engineering and Information Technology. Uploaded in accordance with the publisher's self-archiving policy.
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 20 Jan 2012 10:14
Last Modified: 15 Sep 2014 03:44
Published Version: http://dx.doi.org/10.1016/S1570-6672(09)60026-X
Status: Published
Publisher: Elsevier B.V.
Identification Number: 10.1016/S1570-6672(09)60026-X
URI: http://eprints.whiterose.ac.uk/id/eprint/43635

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