Dealing with Error Recovery in Traffic Flow Prediction Using Bayesian Networks Based on License Plate Scanning Data
Publication: Journal of Transportation Engineering
Volume 137, Issue 9
Abstract
This paper deals with the error recovery problem when scanned license plate data are used to predict traffic flows. The aim is to reduce the effects of errors owing to lost plates or mistaken transcription, to improve estimation results. To this end, a method is given and discussed for traffic flow prediction using plate scanning data and taking into account possible errors in plate number recognition. The proposed method uses Bayesian networks because this is an efficient tool for introducing the plate scan error flow as a variable in the model and mending the mistakes in the scan pattern. Several examples are used to illustrate the proposed model. Finally, some conclusions are included.
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Acknowledgments
The authors are grateful to the Editor and the two anonymous reviewers for their constrictive comments, which led to an improvement of the paper. We would also like to acknowledge Ana Rivas and Inmaculada Gallego for their very useful suggestions and comments on this paper.
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Information
Published In
Journal of Transportation Engineering
Volume 137 • Issue 9 • September 2011
Pages: 615 - 629
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Apr 11, 2010
Accepted: Nov 1, 2010
Published online: Dec 8, 2010
Published in print: Sep 1, 2011
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