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Conference Paper: Determination of optimal successor function in phase-based control using neural network

TitleDetermination of optimal successor function in phase-based control using neural network
Authors
Issue Date1996
PublisherIEEE.
Citation
Ieee Intelligent Vehicles Symposium, Proceedings, 1996, p. 120-125 How to Cite?
AbstractA phase-based method for fixed-time signal control of traffic improves significantly the junction performance over conventional stage-based method of control due to the higher flexibility in specification of signal timings, where the control variables comprise the start and duration of green phases and the cycle time at which the junction is operated. The cycle-structure is specified by a successor function, a combination of 0 and 1 for all incompatible pairs of phases, which indicates the order of phases in a cycle. Normal procedure optimises the timings for each of these successor functions to determine the best timing plan. The computing time is found to be approximately proportional the number of such functions. To reduce the computational requirement, and hence enhance its applicability to real-time actuated control, a neural network is employed in this paper to help identify the optimal successor function for further optimization of timings. Encouraging results are obtained.
Persistent Identifierhttp://hdl.handle.net/10722/47060

 

DC FieldValueLanguage
dc.contributor.authorWong, SCen_HK
dc.contributor.authorLaw, WHen_HK
dc.contributor.authorTong, COen_HK
dc.date.accessioned2007-10-30T07:05:48Z-
dc.date.available2007-10-30T07:05:48Z-
dc.date.issued1996en_HK
dc.identifier.citationIeee Intelligent Vehicles Symposium, Proceedings, 1996, p. 120-125en_HK
dc.identifier.urihttp://hdl.handle.net/10722/47060-
dc.description.abstractA phase-based method for fixed-time signal control of traffic improves significantly the junction performance over conventional stage-based method of control due to the higher flexibility in specification of signal timings, where the control variables comprise the start and duration of green phases and the cycle time at which the junction is operated. The cycle-structure is specified by a successor function, a combination of 0 and 1 for all incompatible pairs of phases, which indicates the order of phases in a cycle. Normal procedure optimises the timings for each of these successor functions to determine the best timing plan. The computing time is found to be approximately proportional the number of such functions. To reduce the computational requirement, and hence enhance its applicability to real-time actuated control, a neural network is employed in this paper to help identify the optimal successor function for further optimization of timings. Encouraging results are obtained.en_HK
dc.format.extent516363 bytes-
dc.format.extent1787 bytes-
dc.format.extent2264 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Intelligent Vehicles Symposium, Proceedingsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©1996 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.titleDetermination of optimal successor function in phase-based control using neural networken_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWong, SC:hhecwsc@hku.hken_HK
dc.identifier.emailTong, CO:cotong@hku.hken_HK
dc.identifier.authorityWong, SC=rp00191en_HK
dc.identifier.authorityTong, CO=rp00178en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IVS.1996.566364en_HK
dc.identifier.scopuseid_2-s2.0-0030408046en_HK
dc.identifier.hkuros20875-
dc.identifier.spage120en_HK
dc.identifier.epage125en_HK
dc.identifier.scopusauthoridWong, SC=24323361400en_HK
dc.identifier.scopusauthoridLaw, WH=7103147821en_HK
dc.identifier.scopusauthoridTong, CO=7202715087en_HK

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