guest ::
| Home > Publications database > Special Issue on Vehicular and Pedestrian Traffic Flow from Data to Models > print |
| Home > Publications database > Special Issue on Vehicular and Pedestrian Traffic Flow from Data to Models > print |
| 001 | 857145 | ||
| 005 | 20210129235509.0 | ||
| 024 | 7 | _ | |a 10.1080/23249935.2018.1441921 |2 doi |
| 024 | 7 | _ | |a 1812-8602 |2 ISSN |
| 024 | 7 | _ | |a 1944-0987 |2 ISSN |
| 024 | 7 | _ | |a 2324-9935 |2 ISSN |
| 024 | 7 | _ | |a 2324-9943 |2 ISSN |
| 024 | 7 | _ | |a WOS:000427920200001 |2 WOS |
| 024 | 7 | _ | |a altmetric:43676520 |2 altmetric |
| 037 | _ | _ | |a FZJ-2018-06389 |
| 082 | _ | _ | |a 380 |
| 100 | 1 | _ | |a Knoop, Victor L. |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Special Issue on Vehicular and Pedestrian Traffic Flow from Data to Models |
| 260 | _ | _ | |a Abingdon |c 2018 |b Taylor & Francis |
| 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 1542115398_11588 |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 We are happy to present this special issue of Transportmetrica A on “Vehicular and pedestrian flow: from data to models”. It bundles eight papers, which describe the ever progressing state-of-the-art in this field. The methods which become available to model and the data collection techniques do change this field rapidly, which makes it possible to more accurately describe traffic flows. We have six papers on pedestrian dynamics and two papers on car traffic dynamics.The first paper “Microscopic travel time analysis of bottleneck experiments” by Bukáček, Hrabák and Krbálek discusses the effect of queuing from the lowest level: they report on experiments they did on pedestrians passing a single bottleneck. This is the first step in the process from data to models.The second paper, by Handel and Borrmann, discusses the next step. Their paper “Service bottlenecks in pedestrian dynamics” compares the bottlenecks both in real-world and in computational models. They conclude that the feedback in the queuing system, increasing efficiency in high-demand situations, is essential.Where the first two papers are focused on a bottleneck, the next two add a network component. This covers a complexity which is typical for pedestrian models, being route choice, i.e. the planned path in complex spatial structures like cities, airports or museums. The third paper of the special issue is “A unified pedestrian routing model for graph-based navigation built on cognitive principles”, by Kielar, Biedermann, Kneidl and Borrmann. The paper presents a methodology to describe routing including spatial as well as social-cognitive aspects |
| 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 Daamen, Winnie |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Schadschneider, Andreas |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Seyfried, Armin |0 P:(DE-Juel1)132266 |b 3 |u fzj |
| 773 | _ | _ | |a 10.1080/23249935.2018.1441921 |g Vol. 14, no. 5-6, p. 373 - 374 |0 PERI:(DE-600)2719295-7 |n 5-6 |p 373 - 374 |t Transportmetrica / A Transport science A |v 14 |y 2018 |x 2324-9943 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/857145/files/Special%20Issue%20on%20Vehicular%20and%20Pedestrian%20Traffic%20Flow%20from%20Data%20to%20Models-1.pdf |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/857145/files/Special%20Issue%20on%20Vehicular%20and%20Pedestrian%20Traffic%20Flow%20from%20Data%20to%20Models-1.pdf?subformat=pdfa |x pdfa |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:857145 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |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 2018 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b TRANSPORTMETRICA A : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 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)0130 |2 StatID |b Social Sciences Citation Index |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1180 |2 StatID |b Current Contents - Social and Behavioral Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |
| 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 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|