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001050075 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-05783
001050075 037__ $$aFZJ-2025-05783
001050075 041__ $$aEnglish
001050075 1001_ $$0P:(DE-Juel1)132266$$aSeyfried, Armin$$b0$$ufzj
001050075 1112_ $$aSimulation of Urban MObility$$cBerlin$$d2025-05-12 - 2025-05-14$$gSUMO$$wGermany
001050075 245__ $$aMovement and waiting of crowds – state of the art models and data
001050075 260__ $$c2025
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001050075 520__ $$aThe 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.
001050075 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001050075 8564_ $$uhttps://juser.fz-juelich.de/record/1050075/files/20250513_SuMo_Seyfried.pdf$$yOpenAccess
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001050075 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132266$$aForschungszentrum Jülich$$b0$$kFZJ
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001050075 9141_ $$y2025
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