Computer simulations are increasingly used to monitor and predict behavior at large crowd events, such as mass gatherings, festivals and evacuations. We critically examine the crowd modeling literature and call for future simulations of crowd behavior to be based more closely on findings from current social psychological research. A systematic review was conducted on the crowd modeling literature ( = 140 articles) to identify the assumptions about crowd behavior that modelers use in their simulations. Articles were coded according to the way in which crowd structure was modeled. It was found that 2 broad types are used: mass approaches and small group approaches. However, neither the mass nor the small group approaches can accurately simulate the large collective behavior that has been found in extensive empirical research on crowd events. We argue that to model crowd behavior realistically, simulations must use methods which allow crowd members to identify with each other, as suggested by self-categorization theory.
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http://dx.doi.org/10.1037/gpr0000032 | DOI Listing |
Sensors (Basel)
December 2024
Department of Engineering, University of Exeter, Exeter EX4 4QF, UK.
A rapidly growing body of experimental evidence in the literature shows that the effects of humans interacting with vibrating structures, other humans, and their surrounding environment can be critical for reliable estimation of structural vibrations. The Interaction-based Vibration Serviceability Assessment framework (I-VSA) was proposed by the authors in 2017 to address this, taking into account human-structure dynamic interactions (HSI) to simulate the structural vibrations experienced by each occupant/pedestrian. The I-VSA method, however, had limited provisions to simulate simultaneously multiple modes of structure in HSI, to simulate human-human and human-environment interactions, and the movement pattern of the occupants/pedestrians.
View Article and Find Full Text PDFMath Biosci
January 2025
Department of Mathematics, University of Houston, Houston, TX, 77204, USA; Department of Biology and Biochemistry, University of Houston, Houston, TX, 77204, USA.
Foraging strategies are shaped by interactions with the environment, and evolve under metabolic constraints. Optimal strategies for isolated and competing organisms have been studied extensively in the absence of evolution. Much less is understood about how metabolic constraints shape the evolution of an organism's ability to detect and reach food.
View Article and Find Full Text PDFInt Emerg Nurs
January 2025
CREAGEN - Environmental, Genetic and Nutritional Epidemiology Research Center, Section of Public Health, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; School of Public Health, University of Berkeley, Berkeley, CA, USA. Electronic address:
Background: Crowding and patient flow management are among the most relevant issues for emergency departments (EDs). This results in delayed treatment, adverse outcomes and increased costs. For these reasons, nurse-independent treatment protocols were developed aimed at managing non-emergency patients outside EDs thus improving patient flow.
View Article and Find Full Text PDFAtten Percept Psychophys
January 2025
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, USA.
As mazes are typically complex, cluttered stimuli, solving them is likely limited by visual crowding. Thus, several aspects of the appearance of the maze - the thickness, spacing, and curvature of the paths, as well as the texture of both paths and walls - likely influence the performance. In the current study, we investigate the effects of perceptual aspects of maze design on maze-solving performance to understand the role of crowding and visual complexity.
View Article and Find Full Text PDFPsychon Bull Rev
January 2025
Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France.
It is striking that visual attention, the process by which attentional resources are allocated in the visual field so as to locally enhance visual perception, is a pervasive component of models of eye movements in reading, but is seldom considered in models of isolated word recognition. We describe BRAID, a new Bayesian word-Recognition model with Attention, Interference and Dynamics. As most of its predecessors, BRAID incorporates three sensory, perceptual, and orthographic knowledge layers together with a lexical membership submodel.
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