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Conference Paper: 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 Date1995
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25
Citation
Vehicle Navigation And Information Systems Conference (Vnis), 1995, p. 75-82 How to Cite?
AbstractThe objective of this work is to model the driver behaviour in the area of route selection. The research focus 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 route candidate has a set of attributes. A fuzzy-neural 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 fuzzy-neural 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/10722/42826
ISSN
2015 Impact Factor: 2.243
2015 SCImago Journal Rankings: 1.203

 

DC FieldValueLanguage
dc.contributor.authorPang, Gen_HK
dc.contributor.authorTakahashi, Ken_HK
dc.contributor.authorYokota, Ten_HK
dc.contributor.authorTakenaga, Hen_HK
dc.date.accessioned2007-03-23T04:32:55Z-
dc.date.available2007-03-23T04:32:55Z-
dc.date.issued1995en_HK
dc.identifier.citationVehicle Navigation And Information Systems Conference (Vnis), 1995, p. 75-82en_HK
dc.identifier.issn0018-9545en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42826-
dc.description.abstractThe objective of this work is to model the driver behaviour in the area of route selection. The research focus 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 route candidate has a set of attributes. A fuzzy-neural 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 fuzzy-neural net on the driver's choice, the route selection function can be made adaptive to the decision-making of the driver.en_HK
dc.format.extent216693 bytes-
dc.format.extent28160 bytes-
dc.format.extent961133 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.format.mimetypeapplication/pdf-
dc.languageengen_HK
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25en_HK
dc.relation.ispartofVehicle Navigation and Information Systems Conference (VNIS)en_HK
dc.rights©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleAdaptive route selection for dynamic route guidance system based on fuzzy-neural approachesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0018-9545&volume=48&issue=6&spage=2028&epage=2041&date=1999&atitle=Adaptive+route+selection+for+dynamic+route+guidance+system+based+on+fuzzy-neural+approachesen_HK
dc.identifier.emailPang, G:gpang@eee.hku.hken_HK
dc.identifier.authorityPang, G=rp00162en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.scopuseid_2-s2.0-0029201810en_HK
dc.identifier.hkuros50481-
dc.identifier.spage75en_HK
dc.identifier.epage82en_HK
dc.identifier.scopusauthoridPang, G=7103393283en_HK
dc.identifier.scopusauthoridTakahashi, K=7409416731en_HK
dc.identifier.scopusauthoridYokota, T=7402558317en_HK
dc.identifier.scopusauthoridTakenaga, H=7006039354en_HK

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