001019420 001__ 1019420
001019420 005__ 20231220201929.0
001019420 0247_ $$2doi$$a10.1103/PhysRevE.108.044302
001019420 0247_ $$2ISSN$$a2470-0045
001019420 0247_ $$2ISSN$$a2470-0061
001019420 0247_ $$2ISSN$$a1063-651X
001019420 0247_ $$2ISSN$$a1095-3787
001019420 0247_ $$2ISSN$$a1538-4519
001019420 0247_ $$2ISSN$$a1539-3755
001019420 0247_ $$2ISSN$$a1550-2376
001019420 0247_ $$2ISSN$$a2470-0053
001019420 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-05377
001019420 037__ $$aFZJ-2023-05377
001019420 082__ $$a530
001019420 1001_ $$0P:(DE-Juel1)180231$$aDahlmanns, Matthias$$b0
001019420 245__ $$aOptimizing the geometry of transportation networks in the presence of congestion
001019420 260__ $$aWoodbury, NY$$bInst.$$c2023
001019420 3367_ $$2DRIVER$$aarticle
001019420 3367_ $$2DataCite$$aOutput Types/Journal article
001019420 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1703071586_18288
001019420 3367_ $$2BibTeX$$aARTICLE
001019420 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001019420 3367_ $$00$$2EndNote$$aJournal Article
001019420 520__ $$aUrban transport systems are gaining in importance, as an increasing share of the global population lives in cities and mobility-based carbon emissions must be reduced to mitigate climate change and improve air quality and citizens' health. As a result, public transport systems are prone to congestion, raising the question of how to optimize them to cope with this challenge. In this paper, we analyze the optimal design of urban transport networks to minimize the average travel time in monocentric as well as in polycentric cities. We suggest an elementary model for congestion and introduce a numerical method to determine the optimal shape among a set of predefined geometries considering different models for the behavior of individual travelers. We map out the optimal shape of fundamental network geometries with a focus on the impact of congestion.
001019420 536__ $$0G:(DE-HGF)POF4-1112$$a1112 - Societally Feasible Transformation Pathways (POF4-111)$$cPOF4-111$$fPOF IV$$x0
001019420 536__ $$0G:(DE-JUEL1)BMBF-03EK3055B$$aCoNDyNet 2 - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (BMBF-03EK3055B)$$cBMBF-03EK3055B$$x1
001019420 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001019420 7001_ $$0P:(DE-Juel1)176610$$aKaiser, Franz$$b1
001019420 7001_ $$0P:(DE-Juel1)162277$$aWitthaut, Dirk$$b2$$eCorresponding author
001019420 773__ $$0PERI:(DE-600)2844562-4$$a10.1103/PhysRevE.108.044302$$gVol. 108, no. 4, p. 044302$$n4$$p044302$$tPhysical review / E$$v108$$x2470-0045$$y2023
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/PhysRevE.108.044302.pdf$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/dahlmanns_optimal_geometry_paper.pdf$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/dahlmanns_optimal_geometry_paper.gif?subformat=icon$$xicon$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/dahlmanns_optimal_geometry_paper.jpg?subformat=icon-1440$$xicon-1440$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/dahlmanns_optimal_geometry_paper.jpg?subformat=icon-180$$xicon-180$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/dahlmanns_optimal_geometry_paper.jpg?subformat=icon-640$$xicon-640$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/PhysRevE.108.044302.gif?subformat=icon$$xicon$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/PhysRevE.108.044302.jpg?subformat=icon-1440$$xicon-1440$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/PhysRevE.108.044302.jpg?subformat=icon-180$$xicon-180$$yOpenAccess
001019420 8564_ $$uhttps://juser.fz-juelich.de/record/1019420/files/PhysRevE.108.044302.jpg?subformat=icon-640$$xicon-640$$yOpenAccess
001019420 909CO $$ooai:juser.fz-juelich.de:1019420$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
001019420 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162277$$aForschungszentrum Jülich$$b2$$kFZJ
001019420 9131_ $$0G:(DE-HGF)POF4-111$$1G:(DE-HGF)POF4-110$$2G:(DE-HGF)POF4-100$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-1112$$aDE-HGF$$bForschungsbereich Energie$$lEnergiesystemdesign (ESD)$$vEnergiesystemtransformation$$x0
001019420 9141_ $$y2023
001019420 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)1230$$2StatID$$aDBCoverage$$bCurrent Contents - Electronics and Telecommunications Collection$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2023-08-29
001019420 915__ $$0LIC:(DE-HGF)APS-112012$$2HGFVOC$$aAmerican Physical Society Transfer of Copyright Agreement
001019420 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPHYS REV E : 2022$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001019420 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-08-29
001019420 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-08-29
001019420 920__ $$lno
001019420 9201_ $$0I:(DE-Juel1)IEK-STE-20101013$$kIEK-STE$$lSystemforschung und Technologische Entwicklung$$x0
001019420 980__ $$ajournal
001019420 980__ $$aVDB
001019420 980__ $$aUNRESTRICTED
001019420 980__ $$aI:(DE-Juel1)IEK-STE-20101013
001019420 9801_ $$aFullTexts