Recursive Prediction of Traffic Conditions with Neural Network Models
Publication: Journal of Transportation Engineering
Volume 126, Issue 6
Abstract
This paper presents a recursive traffic flow prediction algorithm using artificial neural networks. The system prediction model is specified based on the understanding of how disturbances in traffic flow are propagated, and the order of the model is determined by correlation analysis. The parameters of the model, on the other hand, can be obtained through nonlinear optimization. Preliminary studies show that this approach can yield reasonably accurate results.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 126 • Issue 6 • December 2000
Pages: 472 - 481
History
Received: Nov 15, 1998
Published online: Dec 1, 2000
Published in print: Dec 2000
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