Skip to main content
Log in

Design of evacuation strategies with crowd density feedback

基于人群概率密度的拥塞控制设计

  • Research Paper
  • Special Focus on Distributed Control of Nonlinear Multi-Agent Systems and Applications
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

A second-order stochastic model describing a large scale crowd is formulated, and an efficient evacuation strategy for agents in complex surroundings is proposed and solved numerically. The method consists in reshaping the crowd contour by making use of the crowd density feedback that is commonly available from geolocation technologies, and Kantorovich distance is used to transport the current shape into the desired one. The availability of the crowd density enables to solve the otherwise challenging forward-backward problem. Using this approach, we demonstrate via numerical results that the crowd migrates through the complex environment as designed.

中文概要

本文提出了可以描述大规模人群运动的多自体模型,其中每个个体的运动模型由一个二阶随机微分方程来描述,个体之间通过吸引力-排斥力模型相互耦合。从控制人群形状的角度出发设计了在复杂环境中有效防止人群拥塞的反馈控制率。通过数值模拟验证了所提模型的合理性和控制率的有效性。不同于以往的研究,本文首次采用了统计概率密度信息来设计反馈控制率。通过Kantorovich距离比较当前概率密度和目标概率密度,并保证了人群形状的变化在个体移动距离总和的层面上是最优的。该方法有效避免了求解高维耦合Fokker-Planck方程所带来的困难,并且给mean-field模型的研究提供了新思路。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Parrish J, Hammer W. Animal Groups in Three Dimensions. Cambridge: Cambridge University Press, 1997

    Book  Google Scholar 

  2. Balch T, Arkin R C. Behavior-based formation control for multi-robot teams. IEEE Trans Robot Automat, 1998, 14: 926–939

    Article  Google Scholar 

  3. Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic. Nature, 2000, 407: 487–490

    Article  Google Scholar 

  4. Wang J, Zhang L, Shi Q, et al. Modeling and simulating for congestion pedestrian evacuation with panic. Phys A, 2015, 428: 396–409

    Article  Google Scholar 

  5. Twarogowska M, Goatin P, Duvigneau R. Macroscopic modeling and simulations of room evacuation. Appl Math Model, 2014, 38: 5781–5795

    Article  MathSciNet  Google Scholar 

  6. Zheng Y, Jia B, Li X, et al. Evacuation dynamics with fire spreading based on cellular automaton. Phys A, 2011, 390: 3147–3156

    Article  Google Scholar 

  7. Ajzen I. The theory of planned behavior. Organ Behav Hum Decision Process, 1991, 50: 179–211

    Article  Google Scholar 

  8. Sime J D. Crowd psychology and engineering. Saf Sci, 1995, 21: 1–14

    Article  Google Scholar 

  9. Reynolds C W. Flocks, herds, and schools: a distributed behavioral model. Comput Graph, 1987, 21: 25–34

    Article  Google Scholar 

  10. Helbing D, Molnar P. Social force model for pedestrian dynamics. Phys Rev E, 1995, 51: 4282–4286

    Article  Google Scholar 

  11. Gazi V, Passino K M. Stability analysis of swarms. IEEE Trans Automat Contr, 2003, 48: 692–697

    Article  MathSciNet  Google Scholar 

  12. Yang Y, Dimarogonas D V, Hu X. Opinion consensus of modified HegselmannKrause models. Automatica, 2014, 50: 622–627

    Article  MathSciNet  Google Scholar 

  13. Huang M, Caines P E, Malhame R P. Large-population cost-coupled LQG problems with nonuniform agents: individual-mass behavior and decentralized-Nash equilibrium. IEEE Trans Automat Contr, 2007, 52: 1560–1571

    Article  MathSciNet  Google Scholar 

  14. Lasry J, Lions P. Mean field games. Jpn J Math, 2007, 2: 229–260

    Article  MathSciNet  MATH  Google Scholar 

  15. Voorhees P W. The theory of Ostwald ripening. J Statist Phys, 1985, 38: 231–252

    Article  Google Scholar 

  16. Lachapelle A, Wolfram M. On a mean field game approach modeling congestion and aversion in pedestrian crowds. Transp Res Part B, 2011, 45: 1572–1589

    Article  Google Scholar 

  17. Yang Y, Dimarogonas D V, Hu X. Shaping up crowd of agents through controlling their statistical moments. arXiv: 1410.6355 [math.OC]

  18. Elad M, Milanfar R, Golub G H. Shape from moments—an estimation theory perspective. IEEE Trans Signal Process, 2004, 52: 1814–1829

    Article  MathSciNet  Google Scholar 

  19. Yu Y-C. A social interaction system based on cloud computing for mobile video telephony. Sci China Inf Sci, 2014, 57: 032102

    Google Scholar 

  20. Reif J H, Wang H. Social potential fields: a distributed behavioral control for autonomous robots. Robot Auton Syst, 1999, 27: 171–194

    Article  Google Scholar 

  21. Lin Y K, Cai G Q. Probability Structural Dynamic: Advanced Theory and Applications. New York: McGraw-Hill, 2004

    Google Scholar 

  22. Fleming W H, Soner H M. Controlled Markov Process and Viscosity Solutions. New Yourk: Springer, 2006

    MATH  Google Scholar 

  23. Yong J M, Zhou X Y. Stochastic Control, Hamiltonian Systems and HJB Equations. New York: Springer-Verlag, 1999

    MATH  Google Scholar 

  24. Qi L, Cai G Q, Xu W. Nonstationary response of nonlinear oscillators with optimal bounded control and broad0band noises. Probabilistic Eng Mech, 2014, 38: 35–41

    Article  Google Scholar 

  25. Kantorovich L. On the transflocation of masses. Manag Sci, 1958, 5: 1–4

    Article  Google Scholar 

  26. Werman M, Peleg S, Rosenfeld A. A distance metric for multi-dimensional histograms. Comput Vis Graph Image Process, 1985, 32: 328–336

    Article  MATH  Google Scholar 

  27. Kaijse T. Computing the Kantorovich distance for images. J Math Imaging Vision, 1998, 9: 173–191

    Article  MathSciNet  Google Scholar 

  28. Brandt J, Cabrelli C, Molter U. An algorithm for the computation of the Hutchinson distance. Inf Process Lett, 1991, 40: 113–117

    Article  MathSciNet  MATH  Google Scholar 

  29. Deng Y, Du W. The Kantorovich metric in computer science: a brief survey. Electron Notes Theor Comput Sci, 2009, 253: 73–82

    Article  Google Scholar 

  30. Murty K. Linear and Combinatorial Programming. New York: Wiley, 1976

    MATH  Google Scholar 

  31. Gustavi T. Control and coordination of mobile multi-agent systems. Dissertation for the Doctoral Degree. Optimization and Systems Theory, Department of Mathematics, KTH, 2009

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Luyuan Qi or Xiaoming Hu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qi, L., Hu, X. Design of evacuation strategies with crowd density feedback. Sci. China Inf. Sci. 59, 1–11 (2016). https://doi.org/10.1007/s11432-015-5508-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-015-5508-2

Keywords

关键词

Navigation