Journal Home > Volume 27 , Issue 3

With the increase in large-scale incidents in real life, crowd evacuation plays a pivotal role in ensuring the safety of human crowds during emergency situations. The behavior patterns of crowds are well rendered by existing crowd dynamics models. However, most related studies ignore the information perception of pedestrians. To overcome this issue, we develop a visual information based social force model to simulate the interpretable evacuation process from the perspective of visual perception. Numerical experiments indicate that the evacuation efficiency and decision-making ability promote rapidly within a small range with the increase in unbalanced prior knowledge. The propagation of acceleration behavior caused by emergencies is asymmetric due to the anisotropy of visual information. Therefore, this model effectively characterizes the effect of visual information on crowd evacuation and provides new insights into the information perception of individuals in complex scenarios.


menu
Abstract
Full text
Outline
About this article

Visual Information Based Social Force Model for Crowd Evacuation

Show Author's information Wenhan WuMaoyin ChenJinghai LiBinglu LiuXiaolu WangXiaoping Zheng ( )
Department of Automation, Tsinghua University, Beijing 100084, China

Abstract

With the increase in large-scale incidents in real life, crowd evacuation plays a pivotal role in ensuring the safety of human crowds during emergency situations. The behavior patterns of crowds are well rendered by existing crowd dynamics models. However, most related studies ignore the information perception of pedestrians. To overcome this issue, we develop a visual information based social force model to simulate the interpretable evacuation process from the perspective of visual perception. Numerical experiments indicate that the evacuation efficiency and decision-making ability promote rapidly within a small range with the increase in unbalanced prior knowledge. The propagation of acceleration behavior caused by emergencies is asymmetric due to the anisotropy of visual information. Therefore, this model effectively characterizes the effect of visual information on crowd evacuation and provides new insights into the information perception of individuals in complex scenarios.

Keywords: decision-making, crowd evacuation, visual information, social force model

References(29)

[1]
Q. S. Zhang, G. M. Zhao, and J. L. Liu, Performance-based design for large crowd venue control using a multi-agent model, Tsinghua Science and Technology, vol. 14, no. 3, pp. 352-359, 2009.
[2]
A. Bottinelli, D. T. J. Sumpter, and J. L. Silverberg, Emergent structural mechanisms for high-density collective motion inspired by human crowds, Phys. Rev. Lett., vol. 117, no. 22, p. 228301, 2016.
[3]
J. L. Silverberg, M. Bierbaum, J. P. Sethna, and I. Cohen, Collective motion of humans in mosh and circle pits at heavy metal concerts, Phys. Rev. Lett., vol. 110, no. 22, p. 228701, 2013.
[4]
C. Martella, J. Li, C. Conrado, and A. Vermeeren, On current crowd management practices and the need for increased situation awareness, prediction, and intervention, Safety Science, vol. 91, pp. 381-393, 2017.
[5]
M. N. A. Khalid and U. K. Yusof, Dynamic crowd evacuation approach for the emergency route planning problem: Application to case studies, Safety Science, vol. 102, pp. 263-274, 2018.
[6]
F. Q. Tang and A. Z. Ren, Agent-based evacuation model incorporating fire scene and building geometry, Tsinghua Science and Technology, vol. 13, no. 5, pp. 708-714, 2008.
[7]
H. J. Charlesworth and M. S. Turner, Intrinsically motivated collective motion, Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 31, pp. 15362-15367, 2019.
[8]
X. P. Zheng, T. K. Zhong, and M. T. Liu, Modeling crowd evacuation of abuilding based on seven methodological approaches, Building and Environment, vol. 44, no. 3, pp. 437-445, 2009.
[9]
D. Helbing and P. Molnár, Social force model for pedestrian dynamics, Phys. Rev. E, vol. 51, no. 5, pp. 4282-4286, 1995.
[10]
D. Helbing, I. Farkas, and T. Vicsek, Simulating dynamical features of escape panic, Nature, vol. 407, no. 6803, pp. 487-490, 2000.
[11]
L. Zhao, G. Yang, W. Wang, Y. Chen, J. P. Huang, H. Ohashi, and H. E. Stanley, Herd behavior in a complex adaptive system, Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 37, pp. 15058-15063, 2011.
[12]
W. J. Yu and A. Johansson, Modeling crowd turbulence by many-particle simulations, Phys. Rev. E, vol. 76, no. 4 Pt 2, p. 046105, 2007.
[13]
M. Spering and H. M. Chow, Rapid assessment of natural visual motion integration across primate species, Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 44, pp. 11112-11114, 2018.
[14]
L. Y. Deng, M. Yang, Z. D. Liang, Y. S. He, and C. X. Wang, Fusing geometrical and visual information via superpoints for the semantic segmentation of 3D road scenes, Tsinghua Science and Technology, vol. 25, no. 4, pp. 498-507, 2020.
[15]
J. J. Lin, L. Y. Liang, X. Han, C. Yang, X. G. Chen, and X. R. Gao, Cross-target transfer algorithm based on the volterra model of SSVEP-BCI, Tsinghua Science and Technology, vol. 26, no. 4, pp. 505-522, 2021.
[16]
R. Bastien and P. Romanczuk, A model of collective behavior based purely on vision, Science Advances, vol. 6, no. 6, p. eaay0792, 2020.
[17]
B. H. Lemasson, J. J. Anderson, and R. A. Goodwin, Collective motion in animal groups from a neurobiological perspective: The adaptive benefits of dynamic sensory loads and selective attention, Journal of Theoretical Biology, vol. 261, no. 4, pp. 501-510, 2009.
[18]
H. Kuang, T. Chen, X. L. Li, and S. M. Lo, A new lattice hydrodynamic model for bidirectional pedestrian flow considering the visual field effect, Nonlinear Dynamics, vol. 78, no. 3, pp. 1709-1716, 2014.
[19]
X. X. Jian, S. C. Wong, P. Zhang, K. Choi, H. Li, and X. N. Zhang, Perceived cost potential field cellular automata model with an aggregated force field for pedestrian dynamics, Transportation Research Part C: Emerging Technologies, vol. 42, pp. 200-210, 2014.
[20]
M. Moussaïd, D. Helbing, S. Garnier, A. Johansson, M. Combe, andG. Theraulaz, Experimental study of the behavioural mechanisms underlying self-organization in human crowds, Proceedings of the Royal Society B: Biological Sciences, vol. 276, no. 1668, pp. 2755-2762, 2009.
[21]
M. Moussaïd, D. Helbing, and G. Theraulaz, How simple rules determine pedestrian behavior and crowd disasters, Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 17, pp. 6884-6888, 2011.
[22]
S. B. Rosenthal, C. R. Twomey, A. T. Hartnett, H. S. Wu, and I. D. Couzin, Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion, Proceedings of the National Academy of Sciences of the United States of America, vol. 112, no. 15, pp. 4690-4695, 2015.
[23]
B. Collignon, A. Séguret, and J. Halloy, A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments, Royal Society Open Science, vol. 3, no. 1, p. 150473, 2016.
[24]
H. T. Lin, I. G. Ros, and A. A. Biewener, Through the eyes of a bird: Modelling visually guided obstacle flight, Journal of the Royal Society Interface, vol. 11, no. 96, p. 20140239, 2013.
[25]
A. Seyfried, B. Steffen, and T. Lippert, Basics of modelling the pedestrian flow, Physica A: Statistical Mechanics and Its Applications, vol. 368, no. 1, pp. 232-238, 2006.
[26]
M. Moussaïd, N. Perozo, S. Garnier, D. Helbing, and G. Theraulaz,The walking behaviour of pedestrian social groups and its impact on crowd dynamics, PLoS ONE, vol. 5, no. 4, p. e10047, 2010.
[27]
D. J. G. Pearce, A. M. Miller, G. Rowlands, and M. S. Turner, Role of projection in the control of bird flocks, Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 29, pp. 10422-10426, 2014.
[28]
B. W. Jin, J. H. Wang, Y. Wang, Y. M. Gu, and Z. R. Wang, Temporal and spatial distribution of pedestrians in subway evacuation under node failure by multi-hazards, Safety Science, vol. 127, p. 104695, 2020.
[29]
N. Shiwakoti, X. M. Shi, and Z. R. Ye, A review on the performance of an obstacle near an exit on pedestrian crowd evacuation, Safety Science, vol. 113, pp. 54-67, 2019.
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 05 January 2021
Revised: 01 March 2021
Accepted: 15 March 2021
Published: 13 November 2021
Issue date: June 2022

Copyright

© The author(s) 2022

Acknowledgements

This work was supported by the National Key Research and Development Program of China (No. 2020YFF0304900) and the National Major Scientific Research Instrument Development Project of China (No. 61927804).

Rights and permissions

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return