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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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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. |
format | Online Article Text |
id | pubmed-7806084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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