Ekpenyong, Frank and Brimicombe, Allan J. and Palmer-Brown, Dominic and Li, Yang and Lee, Sin Wee (2007) ‘Automated updating of road network databases: road segment grouping using snap-drift neural network’, Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 2nd Annual Conference. University of East London, pp. 160-167.
Ekpenyong, F (2007) AC&T 160-7.pdf - Published Version
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Presented in this paper is a major step towards an innovative solution of GIS road network databases updating which moves away from existing traditional methods where vendors of road network databases go through the time consuming and logistically challenging process of driving along roads to register changes or GIS road network update methods that are exclusively tied to remote sensing images. Our proposed road database update solution would allow users of GIS road network dependent applications (e.g. in-car navigation system) to passively collect characteristics of any “unknown route” (roads not in the database) on behalf of the provider. These data are transferred back to the provider and inputted into an artificial neural net (ANN) which decides, along with similar track data provided by other service users, whether to automatically update (add) the “unknown road” to the road database on probation allowing subsequent users to see the road on their system and use it if need be. At a later stage when there is enough certainty on road geometry and other characteristics the probationary flag could be lifted and permanently added to the road network database. Towards this novel approach we mimicked two journey scenarios covering two test sites and aimed to group the road segments from the journey into their respective road types using the snap-drift neural network (SDNN). The performance of the SDNN is presented and its potential in the proposed solution is investigated.
|Item Type:||Conference or Event Item (Paper)|
|Additional Information:||Citation: Ekpenyong, F. et al. (2007) ‘Automated updating of road network databases: road segment grouping using snap-drift neural network’ Proceedings of Advances in Computing and Technology, (AC&T) The School of Computing and Technology 2nd Annual Conference, University of East London, pp.160-167.|
|Divisions:||Schools > Architecture Computing and Engineering, School of|
|Depositing User:||Mr Stephen Grace|
|Date Deposited:||21 Jul 2010 15:38|
|Last Modified:||27 Sep 2012 11:59|
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