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Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics

The collective behavior of human crowds often exhibits surprisingly regular patterns of movement. These patterns stem from social interactions between pedestrians such as when individuals imitate others, follow their neighbors, avoid collisions with other pedestrians, or push each other. While some...

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Autores principales: Moussaïd, Mehdi, Schinazi, Victor R., Kapadia, Mubbasir, Thrash, Tyler
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806084/
https://www.ncbi.nlm.nih.gov/pubmed/33500961
http://dx.doi.org/10.3389/frobt.2018.00082
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author Moussaïd, Mehdi
Schinazi, Victor R.
Kapadia, Mubbasir
Thrash, Tyler
author_facet Moussaïd, Mehdi
Schinazi, Victor R.
Kapadia, Mubbasir
Thrash, Tyler
author_sort Moussaïd, Mehdi
collection PubMed
description The collective behavior of human crowds often exhibits surprisingly regular patterns of movement. These patterns stem from social interactions between pedestrians such as when individuals imitate others, follow their neighbors, avoid collisions with other pedestrians, or push each other. While some of these patterns are beneficial and promote efficient collective motion, others can seriously disrupt the flow, ultimately leading to deadly crowd disasters. Understanding the dynamics of crowd movements can help urban planners manage crowd safety in dense urban areas and develop an understanding of dynamic social systems. However, the study of crowd behavior has been hindered by technical and methodological challenges. Laboratory experiments involving large crowds can be difficult to organize, and quantitative field data collected from surveillance cameras are difficult to evaluate. Nevertheless, crowd research has undergone important developments in the past few years that have led to numerous research opportunities. For example, the development of crowd monitoring based on the virtual signals emitted by pedestrians' smartphones has changed the way researchers collect and analyze live field data. In addition, the use of virtual reality, and multi-user platforms in particular, have paved the way for new types of experiments. In this review, we describe these methodological developments in detail and discuss how these novel technologies can be used to deepen our understanding of crowd behavior.
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spelling pubmed-78060842021-01-25 Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics Moussaïd, Mehdi Schinazi, Victor R. Kapadia, Mubbasir Thrash, Tyler Front Robot AI Robotics and AI The collective behavior of human crowds often exhibits surprisingly regular patterns of movement. These patterns stem from social interactions between pedestrians such as when individuals imitate others, follow their neighbors, avoid collisions with other pedestrians, or push each other. While some of these patterns are beneficial and promote efficient collective motion, others can seriously disrupt the flow, ultimately leading to deadly crowd disasters. Understanding the dynamics of crowd movements can help urban planners manage crowd safety in dense urban areas and develop an understanding of dynamic social systems. However, the study of crowd behavior has been hindered by technical and methodological challenges. Laboratory experiments involving large crowds can be difficult to organize, and quantitative field data collected from surveillance cameras are difficult to evaluate. Nevertheless, crowd research has undergone important developments in the past few years that have led to numerous research opportunities. For example, the development of crowd monitoring based on the virtual signals emitted by pedestrians' smartphones has changed the way researchers collect and analyze live field data. In addition, the use of virtual reality, and multi-user platforms in particular, have paved the way for new types of experiments. In this review, we describe these methodological developments in detail and discuss how these novel technologies can be used to deepen our understanding of crowd behavior. Frontiers Media S.A. 2018-07-13 /pmc/articles/PMC7806084/ /pubmed/33500961 http://dx.doi.org/10.3389/frobt.2018.00082 Text en Copyright © 2018 Moussaïd, Schinazi, Kapadia and Thrash. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Moussaïd, Mehdi
Schinazi, Victor R.
Kapadia, Mubbasir
Thrash, Tyler
Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title_full Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title_fullStr Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title_full_unstemmed Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title_short Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics
title_sort virtual sensing and virtual reality: how new technologies can boost research on crowd dynamics
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806084/
https://www.ncbi.nlm.nih.gov/pubmed/33500961
http://dx.doi.org/10.3389/frobt.2018.00082
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