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Article: A multi-class traffic flow model - An extension of LWR model with heterogeneous drivers

TitleA multi-class traffic flow model - An extension of LWR model with heterogeneous drivers
Authors
KeywordsHeterogeneous drivers
Macroscopic model
Multi-class
Numerical simulation
Traffic flow
Issue Date2002
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/tra
Citation
Transportation Research Part A: Policy And Practice, 2002, v. 36 n. 9, p. 827-841 How to Cite?
AbstractIn this paper, a multi-class traffic flow model as an extension of the Lighthill, Whitham and Richards (LWR) model with heterogeneous drivers is formulated. The model takes into account the distribution of heterogeneous drivers characterized by their choice of speeds in a traffic streams, which models the dynamic behavior of heterogeneous users whereby faster vehicles could overtake slower ones under uncongested condition as well as congested condition (though less easily), and slower vehicles would slow down the faster ones. Numerical simulations show that the model can predict many of the puzzling traffic flow phenomena such as the two-capacity (or reverse-lambda) regimes occurred in the fundamental diagram, hysteresis and platoon dispersion. © 2002 Elsevier Science Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/71614
ISSN
2023 Impact Factor: 6.3
2023 SCImago Journal Rankings: 2.182
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWong, GCKen_HK
dc.contributor.authorWong, SCen_HK
dc.date.accessioned2010-09-06T06:33:35Z-
dc.date.available2010-09-06T06:33:35Z-
dc.date.issued2002en_HK
dc.identifier.citationTransportation Research Part A: Policy And Practice, 2002, v. 36 n. 9, p. 827-841en_HK
dc.identifier.issn0965-8564en_HK
dc.identifier.urihttp://hdl.handle.net/10722/71614-
dc.description.abstractIn this paper, a multi-class traffic flow model as an extension of the Lighthill, Whitham and Richards (LWR) model with heterogeneous drivers is formulated. The model takes into account the distribution of heterogeneous drivers characterized by their choice of speeds in a traffic streams, which models the dynamic behavior of heterogeneous users whereby faster vehicles could overtake slower ones under uncongested condition as well as congested condition (though less easily), and slower vehicles would slow down the faster ones. Numerical simulations show that the model can predict many of the puzzling traffic flow phenomena such as the two-capacity (or reverse-lambda) regimes occurred in the fundamental diagram, hysteresis and platoon dispersion. © 2002 Elsevier Science Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/traen_HK
dc.relation.ispartofTransportation Research Part A: Policy and Practiceen_HK
dc.subjectHeterogeneous driversen_HK
dc.subjectMacroscopic modelen_HK
dc.subjectMulti-classen_HK
dc.subjectNumerical simulationen_HK
dc.subjectTraffic flowen_HK
dc.titleA multi-class traffic flow model - An extension of LWR model with heterogeneous driversen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0965-8564&volume=36&spage=827&epage=841&date=2002&atitle=A+multi-class+traffic+flow+model+-+an+extension+of+LWR+model+with+heterogeneous+driversen_HK
dc.identifier.emailWong, SC:hhecwsc@hku.hken_HK
dc.identifier.authorityWong, SC=rp00191en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S0965-8564(01)00042-8en_HK
dc.identifier.scopuseid_2-s2.0-0036832844en_HK
dc.identifier.hkuros75990en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036832844&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume36en_HK
dc.identifier.issue9en_HK
dc.identifier.spage827en_HK
dc.identifier.epage841en_HK
dc.identifier.isiWOS:000177662200005-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridWong, GCK=7402527086en_HK
dc.identifier.scopusauthoridWong, SC=24323361400en_HK
dc.identifier.issnl0965-8564-

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