001     151997
005     20210129213633.0
024 7 _ |a 10.1016/j.physa.2014.03.004
|2 doi
024 7 _ |a WOS:000337854200032
|2 WOS
024 7 _ |a altmetric:1967986
|2 altmetric
037 _ _ |a FZJ-2014-01821
041 _ _ |a English
082 _ _ |a 500
100 1 _ |a Zhang, Jun
|0 P:(DE-Juel1)156196
|b 0
|e Corresponding Author
|u fzj
245 _ _ |a Comparison of intersecting pedestrian flows based on experiments
260 _ _ |a Amsterdam
|c 2014
|b North Holland Publ. Co.
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1396421701_15674
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
520 _ _ |a Intersections of pedestrian flows feature multiple types, varying in the numbers of flow directions as well as intersecting angles. In this article results from intersecting flow experiments with two different intersecting angles are compared. To analyze the transport capabilities the Voronoi method is used to resolve the fine structure of the resulting velocity–density relations and spatial dependence of the measurements. The fundamental diagrams of various flow types are compared and show no apparent difference with respect to the intersecting angle 90° and 180°. This result indicates that head-on conflicts of different types of flow have the same influence on the transport properties of the system, which demonstrates the high self-organization capabilities of pedestrians.
536 _ _ |a 411 - Computational Science and Mathematical Methods (POF2-411)
|0 G:(DE-HGF)POF2-411
|c POF2-411
|f POF II
|x 0
700 1 _ |a Seyfried, Armin
|0 P:(DE-Juel1)132266
|b 1
|u fzj
773 _ _ |a 10.1016/j.physa.2014.03.004
|0 PERI:(DE-600)1466577-3
|p 316–325
|t Physica / A
|v 405
|y 2014
|x 0378-4371
856 4 _ |u https://juser.fz-juelich.de/record/151997/files/FZJ-2014-01821.pdf
|y Restricted
909 C O |o oai:juser.fz-juelich.de:151997
|p VDB
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)156196
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)132266
913 2 _ |a DE-HGF
|b Key Technologies
|l Supercomputing & Big Data
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|2 G:(DE-HGF)POF3-500
|v Computational Science and Mathematical Methods
|x 0
913 1 _ |a DE-HGF
|b Schlüsseltechnologien
|l Supercomputing
|1 G:(DE-HGF)POF2-410
|0 G:(DE-HGF)POF2-411
|2 G:(DE-HGF)POF2-400
|v Computational Science and Mathematical Methods
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF2
914 1 _ |y 2014
915 _ _ |a JCR/ISI refereed
|0 StatID:(DE-HGF)0010
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21