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Article: Adaptive route selection for dynamic route guidance system based on fuzzy-neural approaches

TitleAdaptive route selection for dynamic route guidance system based on fuzzy-neural approaches
Authors
Issue Date1999
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25
Citation
Ieee Transactions On Vehicular Technology, 1999, v. 48 n. 6, p. 2028-2041 How to Cite?
AbstractOne functionality of an in-vehicle navigation system is route planning. Given a set of origin-destination (O/D) pairs, there could be many possible routes for a driver. A useful routing system should have the capability to support the driver effectively in deciding on an optimum route to his preference. The objective of this work is to model the driver behavior in the area of route selection. In particular, the research focuses on an optimum route search function in a typical in-car navigation system or dynamic route guidance (DRG) system. In this work, we want to emphasize the need to orientate the route selection method on the driver's preference. Each feasible route has a set of attributes. A fuzzy-neural (FN) approach is used to represent the correlation of the attributes with the driver's route selection. A recommendation or route ranking can be provided to the driver. Based on a training of the FN net on the driver's choice, the route selection function can be made adaptive to the decision making of the driver.
Persistent Identifierhttp://hdl.handle.net/10722/155117
ISSN
2015 Impact Factor: 2.243
2015 SCImago Journal Rankings: 1.203
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorPang, GKHen_US
dc.contributor.authorTakahashi, Ken_US
dc.contributor.authorYokota, Ten_US
dc.contributor.authorTakenaga, Hen_US
dc.date.accessioned2012-08-08T08:31:56Z-
dc.date.available2012-08-08T08:31:56Z-
dc.date.issued1999en_US
dc.identifier.citationIeee Transactions On Vehicular Technology, 1999, v. 48 n. 6, p. 2028-2041en_US
dc.identifier.issn0018-9545en_US
dc.identifier.urihttp://hdl.handle.net/10722/155117-
dc.description.abstractOne functionality of an in-vehicle navigation system is route planning. Given a set of origin-destination (O/D) pairs, there could be many possible routes for a driver. A useful routing system should have the capability to support the driver effectively in deciding on an optimum route to his preference. The objective of this work is to model the driver behavior in the area of route selection. In particular, the research focuses on an optimum route search function in a typical in-car navigation system or dynamic route guidance (DRG) system. In this work, we want to emphasize the need to orientate the route selection method on the driver's preference. Each feasible route has a set of attributes. A fuzzy-neural (FN) approach is used to represent the correlation of the attributes with the driver's route selection. A recommendation or route ranking can be provided to the driver. Based on a training of the FN net on the driver's choice, the route selection function can be made adaptive to the decision making of the driver.en_US
dc.languageengen_US
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25en_US
dc.relation.ispartofIEEE Transactions on Vehicular Technologyen_US
dc.titleAdaptive route selection for dynamic route guidance system based on fuzzy-neural approachesen_US
dc.typeArticleen_US
dc.identifier.emailPang, GKH:gpang@eee.hku.hken_US
dc.identifier.authorityPang, GKH=rp00162en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/25.806795en_US
dc.identifier.scopuseid_2-s2.0-0033341407en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0033341407&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume48en_US
dc.identifier.issue6en_US
dc.identifier.spage2028en_US
dc.identifier.epage2041en_US
dc.identifier.isiWOS:000084046200030-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridPang, GKH=7103393283en_US
dc.identifier.scopusauthoridTakahashi, K=7409416731en_US
dc.identifier.scopusauthoridYokota, T=7402558317en_US
dc.identifier.scopusauthoridTakenaga, H=7006039354en_US

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