Lancaster EPrints

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.

Full text not available from this repository.

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: Article
Journal or Publication Title: International Journal of Forecasting
Uncontrolled Keywords: Motorway networks ; Traffic dynamics ; State-space model ; Kalman filter ; Independence graph
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 19530
Deposited By: ep_ss_importer
Deposited On: 13 Nov 2008 16:47
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:31
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/19530

Actions (login required)

View Item