Literature DB >> 30606837

Dynamic response and hydrodynamics of polarized crowds.

Nicolas Bain1, Denis Bartolo1.   

Abstract

Modeling crowd motion is central to situations as diverse as risk prevention in mass events and visual effects rendering in the motion picture industry. The difficulty of performing quantitative measurements in model experiments has limited our ability to model pedestrian flows. We use tens of thousands of road-race participants in starting corrals to elucidate the flowing behavior of polarized crowds by probing its response to boundary motion. We establish that speed information propagates over system-spanning scales through polarized crowds, whereas orientational fluctuations are locally suppressed. Building on these observations, we lay out a hydrodynamic theory of polarized crowds and demonstrate its predictive power. We expect this description of human groups as active continua to provide quantitative guidelines for crowd management.
Copyright © 2019, American Association for the Advancement of Science.

Entities:  

Mesh:

Year:  2019        PMID: 30606837     DOI: 10.1126/science.aat9891

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  12 in total

1.  Nonreciprocity as a generic route to traveling states.

Authors:  Zhihong You; Aparna Baskaran; M Cristina Marchetti
Journal:  Proc Natl Acad Sci U S A       Date:  2020-08-04       Impact factor: 11.205

2.  Collective turns in jackdaw flocks: kinematics and information transfer.

Authors:  Hangjian Ling; Guillam E Mclvor; Joseph Westley; Kasper van der Vaart; Jennifer Yin; Richard T Vaughan; Alex Thornton; Nicholas T Ouellette
Journal:  J R Soc Interface       Date:  2019-10-23       Impact factor: 4.118

3.  Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of 'stripe' formation in human data.

Authors:  Pratik Mullick; Sylvain Fontaine; Cécile Appert-Rolland; Anne-Hélène Olivier; William H Warren; Julien Pettré
Journal:  PLoS Comput Biol       Date:  2022-06-09       Impact factor: 4.779

4.  Non-reciprocal phase transitions.

Authors:  Michel Fruchart; Ryo Hanai; Peter B Littlewood; Vincenzo Vitelli
Journal:  Nature       Date:  2021-04-14       Impact factor: 49.962

5.  An equation of state for insect swarms.

Authors:  Michael Sinhuber; Kasper van der Vaart; Yenchia Feng; Andrew M Reynolds; Nicholas T Ouellette
Journal:  Sci Rep       Date:  2021-02-12       Impact factor: 4.379

6.  Estimating density limits for walking pedestrians keeping a safe interpersonal distancing.

Authors:  I Echeverría-Huarte; A Garcimartín; R C Hidalgo; C Martín-Gómez; I Zuriguel
Journal:  Sci Rep       Date:  2021-01-15       Impact factor: 4.379

7.  Markerless tracking of an entire honey bee colony.

Authors:  Alexander S Mikheyev; Greg J Stephens; Katarzyna Bozek; Laetitia Hebert; Yoann Portugal
Journal:  Nat Commun       Date:  2021-03-19       Impact factor: 14.919

8.  Measuring Dynamics in Evacuation Behaviour with Deep Learning.

Authors:  Huaidian Hou; Lingxiao Wang
Journal:  Entropy (Basel)       Date:  2022-01-27       Impact factor: 2.524

9.  Self-organization in natural swarms of Photinus carolinus synchronous fireflies.

Authors:  Raphaël Sarfati; Julie C Hayes; Orit Peleg
Journal:  Sci Adv       Date:  2021-07-07       Impact factor: 14.136

10.  Mechanical spectroscopy of insect swarms.

Authors:  Kasper van der Vaart; Michael Sinhuber; Andrew M Reynolds; Nicholas T Ouellette
Journal:  Sci Adv       Date:  2019-07-10       Impact factor: 14.136

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.