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dc.contributor.authorPassow, Benjamin N.en
dc.contributor.authorElizondo, Daviden
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorWitheridge, S.en
dc.contributor.authorGoodyer, E. N.en
dc.date.accessioned2013-11-12T11:46:19Z
dc.date.available2013-11-12T11:46:19Z
dc.date.issued2013-10
dc.identifier.citationPassow, B. N., Elizondo, D., Chiclana, F., Witheridge, S. and Goodyer, E. (2013) Adapting Traffic Simulation for Traffic Management: A Neural Network Approach. Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems' (ITSC 2013), The Hague, Netherlands, 6-9 October 2013. Article number 6728427, Pages 1402-1407en
dc.identifier.urihttp://hdl.handle.net/2086/9347
dc.description.abstractStatic models and simulations are commonly used in urban traffic management but none feature a dynamic element for near real-time traffic control. This work presents an artificial neural network forecaster methodology applied to traffic flow condition prediction. The spatially distributed architecture uses life-long learning with a novel adaptive Artificial Neural Network based filter to detect and remove outliers from training data. The system has been designed to support traffic engineers in their decision making to react to traffic conditions before they get out of control. We performed experiments using feed-forward backpropagation, cascade-forward back-propagation, radial basis, and generalized regression Artificial Neural Networks for this purpose. Test results on actual data collected from the city of Leicester, UK, confirm our approach to deliver suitable forecasts.en
dc.subjectNeural Networksen
dc.subjectIntelligent Transport Systemsen
dc.subjectTraffic Flow Predictionen
dc.subjectAdaptive Filteren
dc.subjectTraffic Simulationen
dc.titleAdapting Traffic Simulation for Traffic Management: A Neural Network Approachen
dc.typeConferenceen
dc.identifier.doihttp://dx.doi.org/10.1109/ITSC.2013.6728427
dc.researchgroupDIGITSen
dc.researchgroupCentre for Computational Intelligence
dc.peerreviewedYesen
dc.funder-en
dc.projectid-en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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