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| Hauptseite > Publikationsdatenbank > Movement and waiting of crowds – state of the art models and data > print |
| Hauptseite > Publikationsdatenbank > Movement and waiting of crowds – state of the art models and data > print |
| 001 | 1050075 | ||
| 005 | 20251223202202.0 | ||
| 024 | 7 | _ | |a 10.34734/FZJ-2025-05783 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2025-05783 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Seyfried, Armin |0 P:(DE-Juel1)132266 |b 0 |u fzj |
| 111 | 2 | _ | |a Simulation of Urban MObility |g SUMO |c Berlin |d 2025-05-12 - 2025-05-14 |w Germany |
| 245 | _ | _ | |a Movement and waiting of crowds – state of the art models and data |
| 260 | _ | _ | |c 2025 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1766485587_29350 |2 PUB:(DE-HGF) |x Invited |
| 502 | _ | _ | |c DLR |
| 520 | _ | _ | |a The contribution starts with a historical review of the connection between modelling and technical possibilities of data collection. This is followed by an overview of current approaches to modelling the movement of individual pedestrians in crowds. These include cellular automata, force as well as speed models, and trajectory prediction models based on machine learning methods. A classification of individual movement options and collective phenomena in different density ranges is used to critically discuss current model approaches and their advantages and disadvantages. The last part of the lecture is dedicated to empirical results on waiting behaviour and first modelling approaches. The focus is on waiting on platforms and in queueing systems for event venues. |
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| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/1050075/files/20250513_SuMo_Seyfried.pdf |y OpenAccess |
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| 914 | 1 | _ | |y 2025 |
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