Home > Publications database > Analysis of Space Usage on Train Station Platforms Based on Trajectory Data > print |
001 | 885761 | ||
005 | 20210130010512.0 | ||
024 | 7 | _ | |a 10.3390/su12208325 |2 doi |
024 | 7 | _ | |a 2128/25942 |2 Handle |
024 | 7 | _ | |a WOS:000583123600001 |2 WOS |
037 | _ | _ | |a FZJ-2020-04070 |
041 | _ | _ | |a English |
082 | _ | _ | |a 690 |
100 | 1 | _ | |a Küpper, Mira |0 P:(DE-Juel1)176878 |b 0 |e Corresponding author |
245 | _ | _ | |a Analysis of Space Usage on Train Station Platforms Based on Trajectory Data |
260 | _ | _ | |a Basel |c 2020 |b MDPI |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1603258727_6349 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a Functionality of railway platforms could be assessed by Level of Service concepts. They describe interactions between humans and the built environment and allow to rate risks due to overcrowding. To improve existing concepts, a detailed analysis of how pedestrians use the space is performed and new measurement and evaluation methods are introduced. Trajectories of passengers at platforms in Bern and Zurich Hardbrücke (Switzerland) are analysed. Boarding and alighting passengers show different behaviour, considering the travel paths, waiting times and mean speed. Density, speed and flow profiles are exploit and a new measure for the occupation of space is introduced. The Analysis has shown, that it is necessary to filter the data in order to reach a realistic assessment of the Level of Service. Three main factors should be considered: the time of day, the times when trains arrive and depart and the platform side. Therefore, density, speed and flow profiles are averaged over the time of one minute and calculated depending on the train arrival. The methodology developed in this article is the basis for enhanced and more specific Level of Service concepts and offers the possibility to optimise planning of transportation infrastructures with regard to functionality and sustainability. |
536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef |
700 | 1 | _ | |a Seyfried, Armin |0 P:(DE-Juel1)132266 |b 1 |
773 | _ | _ | |a 10.3390/su12208325 |g Vol. 12, no. 20, p. 8325 - |0 PERI:(DE-600)2518383-7 |n 20 |p 8325 - |t Sustainability |v 12 |y 2020 |x 2071-1050 |
856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/885761/files/manuscript.v7-1.pdf |
856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/885761/files/sustainability-12-08325.pdf |
856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/885761/files/manuscript.v7-1.pdf?subformat=pdfa |
856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/885761/files/sustainability-12-08325.pdf?subformat=pdfa |
909 | C | O | |o oai:juser.fz-juelich.de:885761 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)176878 |
910 | 1 | _ | |a BUW: University of Wuppertal |0 I:(DE-HGF)0 |b 0 |6 P:(DE-Juel1)176878 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)132266 |
910 | 1 | _ | |a BUW: University of Wuppertal |0 I:(DE-HGF)0 |b 1 |6 P:(DE-Juel1)132266 |
913 | 1 | _ | |a DE-HGF |b Key Technologies |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 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
914 | 1 | _ | |y 2020 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0130 |2 StatID |b Social Sciences Citation Index |d 2020-01-15 |
915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b SUSTAINABILITY-BASEL : 2018 |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1180 |2 StatID |b Current Contents - Social and Behavioral Sciences |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2020-01-15 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2020-01-15 |
915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-01-15 |
915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2020-01-15 |
915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Blind peer review |d 2020-01-15 |
915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |f 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-01-15 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-01-15 |
920 | 1 | _ | |0 I:(DE-Juel1)IAS-7-20180321 |k IAS-7 |l Zivile Sicherheitsforschung |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a UNRESTRICTED |
980 | _ | _ | |a I:(DE-Juel1)IAS-7-20180321 |
980 | 1 | _ | |a FullTexts |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|