Tracking and predicting a network traffic process.

Garside, S. and Lindveld, K. and Whittaker, J. (1997) Tracking and predicting a network traffic process. International Journal of Forecasting, 13. pp. 51-61.

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Abstract

This article deals with the problem of real-time modelling and prediction of motorway traffic. Conditional independence relationships and ideas of Bayesian forecasting are proposed leading to the employment of dynamic state-space models, with optimal state estimation coming from the Kalman filter. Models, based on classical differential equations, which incorporate representations of the network topology are derived and are implemented in a state-space framework. The model is applied to several road networks in The Netherlands from which encouraging preliminary results are obtained.

Item Type:
Journal Article
Journal or Publication Title:
International Journal of Forecasting
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa
Subjects:
ID Code:
19530
Deposited By:
Deposited On:
13 Nov 2008 16:47
Refereed?:
Yes
Published?:
Published
Last Modified:
26 May 2020 01:39