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Journal ArticleDOI

State-of-the-art crowd motion simulation models

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TLDR
This paper provides a broad, but not exhaustive overview of the crowd motion simulation models of the last decades and argues that any model used for crowd simulation should be able to simulate most of the phenomena indicated in this paper.
Abstract
Currently, pedestrian simulation models are used to predict where, when and why hazardous high density crowd movements arise. However, it is questionable whether models developed for low density situations can be used to simulate high density crowd movements. The objective of this paper is to assess the existent pedestrian simulation models with respect to known crowd phenomena in order to ascertain whether these models can indeed be used for the simulation of high density crowds and to indicate any gaps in the field of pedestrian simulation modeling research. This paper provides a broad, but not exhaustive overview of the crowd motion simulation models of the last decades. It is argued that any model used for crowd simulation should be able to simulate most of the phenomena indicated in this paper. In the paper cellular automata, social force models, velocity-based models, continuum models, hybrid models, behavioral models and network models are discussed. The comparison shows that the models can roughly be divided into slow but highly precise microscopic modeling attempts and very fast but behaviorally questionable macroscopic modeling attempts. Both sets of models have their use, which is highly dependent on the application the model has originally been developed for. Yet, for practical applications, that need both precision and speed, the current pedestrian simulation models are inadequate.

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Citations
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Social Distance Modeling on the Copenhagen, Denmark, Metro

TL;DR: Public transport is a critical service in Copenhagen, Denmark, because many residents do not own a car, and in any event, car travel is not practical in the city center due to narrow roads as discussed by the authors.
Proceedings ArticleDOI

Smart IoT Cameras for Crowd Analysis based on augmentation for automatic pedestrian detection, simulation and annotation

TL;DR: A framework for crowd simulation and automatic data generation and annotation that supports multiple cameras and multiple targets is proposed based on synthetically generated human agents, augmented frames and compositing techniques combined with path finding and planning methods.
Book ChapterDOI

Research on Passenger Flow Distribution in Urban Rail Transit Hub Platform

TL;DR: By case study, the performance comparison between two simulation methods indicates that simulation designs are scientific and accordant with the reality scene.
Dissertation

A Comparative Analysis of Agent-Based Pedestrian Modelling Approaches

Gregory Hoy
TL;DR: Using two transit station scenarios, each model’s ability to match observed and increased volume pedestrian flows is explored and their relative speeds are compared, generally showing significant speed advantages over the default MassMotion model but also indicating that the graph and Optimal Steps models are note sufficiently sensitive to congestion.
Journal ArticleDOI

Dynamic Crowd Accident-Risk Assessment Based on Internal Energy and Information Entropy for Large-Scale Crowd Flow Considering COVID-19 Epidemic

TL;DR: Wang et al. as mentioned in this paper proposed a hybrid crowd accident-risk assessment (HCRA) model based on internal energy and information entropy, which considers not only crowd density but also the modulus and direction of a crowd velocity vector simultaneously.
References
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Journal ArticleDOI

Social Force Model for Pedestrian Dynamics

TL;DR: Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
Journal ArticleDOI

Simulating dynamical features of escape panic

TL;DR: A model of pedestrian behaviour is used to investigate the mechanisms of panic and jamming by uncoordinated motion in crowds, and an optimal strategy for escape from a smoke-filled room is found, involving a mixture of individualistic behaviour and collective ‘herding’ instinct.
Journal ArticleDOI

Traffic and related self-driven many-particle systems

TL;DR: This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic, including microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models.
Book

Relations in Public: Microstudies of the Public Order

TL;DR: For instance, the authors argues that the way strangers relate in public is part of a design by which friends and acquaintances manage their relationship in the presence of bystanders, and argues that, taken together, this forms part of an inquiry into the rules for co-mingling, or public order.
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What is state of the art in crowd simulation?

The paper discusses various crowd motion simulation models, including cellular automata, social force models, velocity-based models, continuum models, hybrid models, behavioral models, and network models.