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The Effects of Detector Spacing on Traffic Forecasting Performance Using Neural Networks

Chen, Haibo; Dougherty, Mark S.; Kirby, Howard R.

Authors

Haibo Chen

Mark S. Dougherty

Howard R. Kirby



Abstract

An investigation was made as to how short-term traffic forecasting on motorways and other trunk roads is related to the density of detectors. Forecasting performances with respect to different detector spaces have been investigated with both simulated data and real data. Pruning techniques to the input variables used for neural networks were applied to the simulated data. The real data were collected from the M25 motorway and included flow, speed, and occupancy. With the data used in our study, the forecasting performances decrease with the increase of detector spaces. However, by taking the assumed costs of detector infrastructure into account, it may be concluded from this study that increasing coverage to a spacing of 500 m gives little extra benefit and may actually be counter productive in certain circumstances. It was concluded that, on the basis of current evidence, a detector spacing of between 1 and 1.5 km might be optimal.

Journal Article Type Article
Online Publication Date Dec 17, 2002
Publication Date 2001-11
Deposit Date Feb 27, 2008
Print ISSN 1093-9687
Electronic ISSN 1467-8667
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 16
Issue 6
Pages 422-430
DOI https://doi.org/10.1111/0885-9507.00244
Keywords Motorways, Road traffic detection, Detector spacing, Large intervals, Decline in predictions, Optimal spacing calculation
Public URL http://researchrepository.napier.ac.uk/id/eprint/1894
Publisher URL http://dx.doi.org/10.1111/0885-9507.00244