001     1029549
005     20241126210227.0
020 _ _ |a 978-3-95806-773-8
024 7 _ |a 10.34734/FZJ-2024-05161
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037 _ _ |a FZJ-2024-05161
100 1 _ |a Üsten, Ezel
|0 P:(DE-Juel1)185878
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245 _ _ |a Dynamic Motivation in Crowds: Insights from Experiments and Pedestrian Models for Goal-Directed Motion
|f - 2024-08-15
260 _ _ |a Jülich
|c 2024
|b Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
300 _ _ |a ix, 121
336 7 _ |a Output Types/Dissertation
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336 7 _ |a Book
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336 7 _ |a DISSERTATION
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336 7 _ |a PHDTHESIS
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336 7 _ |a Dissertation / PhD Thesis
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336 7 _ |a doctoralThesis
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490 0 _ |a Schriften des Forschungszentrums Jülich IAS Series
|v 64
502 _ _ |a Dissertation, Univ. Wuppertal, 2024
|c Univ. Wuppertal
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|d 2024
520 _ _ |a The actions that pedestrians take to reach a destination or move are always influenced by their motivation. Even though motivation has been thoroughly studied in various contexts in psychology, in the context of pedestrian dynamics, it has primarilybeen simplified as a dichotomous parameter, categorized into high and low motivation. However, to gain a comprehensive understanding of pedestrian activities and the consequent safety measures, it is crucial to thoroughly investigate the dynamics of motivation and its associated outcomes, including emotion and behavior. This involves exploring the subject in depth, as it has been studied in other contexts. Doing so will enable researchers within the field to incorporate these psychological characteristics and their relationships into the already established topics within engineering and safety fields. The primary objective of this cumulative thesis is to present recent investigations on motivation topic. To achieve this, four publications are presented (of which three have been published), each exploring motivation as an umbrella concept within pedestrian dynamics context while focusing on motivational outcomes
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
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|v Enabling Computational- & Data-Intensive Science and Engineering
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914 1 _ |y 2024
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920 1 _ |0 I:(DE-Juel1)IAS-7-20180321
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