Skip to main content
SpringerLink
Log in

An Agent-Based Model for Simulating Human-Like Crowd in Dense Places

  • Conference paper
Computational Intelligence and Intelligent Systems (ISICA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 316))

Included in the following conference series:

  • 2252 Accesses

Abstract

Crowd simulation has been becoming an efficient tool to study the crowd behaviour and its movement. Compared with macroscopic model, microscopic model is able to generate a fine grain simulation result. This paper proposes a agent-based model for crowd simulation for dense area. The simulation model considers how agent selects a goal as its moving destination, how avoids collision with neighboured agents, how leads or follow a group of agents, and how avoids high dense area to reduce its traveling time. Simulation results show the proposed agent-based model is able to simulate agent navigating and move around dense simulation environment. The simulation performance is also efficient.

This study was supported in part by National Natural Science Foundation of China (grant No.61103145), and the Fundamental Research Funds for the Central Universities, (China University of Geosciences (Wuhan), No.CUG100314 and No.CUG120409).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dynamics, C.: Crowd disaster (June 2008), http://www.crowddynamics.com/main/crowddisasters.html

  2. Thalmann, D., Musse, S.R.: Crowd Simulation. Springer (2007)

    Google Scholar 

  3. Daly, P., McGrath, F., Annesley, T.: Pedestrian speed/flow relationships for underground stations. Traffic Engineering and Control 32(2), 75–78

    Google Scholar 

  4. Bradley, G.E.: A proposed mathematical model for computer prediction of crowd movements and their associated risks. In: Smith, R.A., Dickie, J.F. (eds.) Proceedings of the International Conference on Engineering for Crowd Safety, pp. 303–311. Elsevier Publishing Company, London (1993)

    Google Scholar 

  5. Tanaka, T.: A study for performance based design of means of escape in fire. In: Cox, G., Langford, B. (eds.) Proceedings of the 3rd International Symposium on Fire Safety Science, pp. 729–738. Elsevier (1991)

    Google Scholar 

  6. Burstedde, C., Klauck, K., Schadschneider, A., Zittartz, J.: Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A: Statistical Mechanics and its Applications 295(3-4), 507–525 (2001)

    Article  MATH  Google Scholar 

  7. Muramatsu, M., Irie, T., Nagatani, T.: Jamming transition in pedestrian counter flow. Physica A: Statistical Mechanics and its Applications 267(3-4), 487–498 (1999)

    Article  Google Scholar 

  8. Nguyen, Q.H., McKenzie, F.D., Petty, M.D.: Crowd behavior cognitive model architecture design. In: Proceedings of the 2005 Behavior Representation in Modeling and Simulation (BRIMS) Conference, Universal City, CA, pp. 55–64 (2005)

    Google Scholar 

  9. Pelechano, N., O’Brien, K., Silverman, B., Badler, N.: Crowd simulation incorporating agent psychological models, roles and communication. In: Proceedings of the First International Workshop on Crowd Simulation, EPFL, Lausanne-Switzerland (November 2005)

    Google Scholar 

  10. Brogan, D., Hodgins, J.: Group behaviors for systems with significant dynamics. Autonomous Robots 4(1), 137–153 (1997)

    Article  Google Scholar 

  11. Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Letters to Nature 407, 487–490 (2000)

    Article  Google Scholar 

  12. Chenney, S.: Flow tiles. In: Proceedings of the 2004 ACM SIGGRAPH/ Eurographics Symposium on Computer Animation, San Diego, California, USA, July 26-27, pp. 233–242 (2004)

    Google Scholar 

  13. Greenshields, B.D.: A study in highway capacity. Highway Research Board Proceedings 14, 448–478 (1934)

    Google Scholar 

  14. Smith, R.A.: Volume flow rate of densely packed crowds. In: Smith, R.A., Dickie, J.F. (eds.) Proceedings of the International Conference on Engineering for Crowd Safety, pp. 313–319. Elsevier Publishing Company, London (1993)

    Google Scholar 

  15. Smith, R.A.: Density, velocity and flow relationships for closely packed crowds. Safety Science 18(4), 321–327 (1995)

    Article  Google Scholar 

  16. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufman, San Mateo (1998)

    Google Scholar 

  17. Zadeh, L.A.: Fuzzy logic. IEEE Computer 22(4), 83–93 (1998)

    Google Scholar 

  18. Hassoun, M.H.: Fundamentals of Artificial Neural Networks. MIT Press (1995)

    Google Scholar 

  19. Rao, A.S., Georgeff, M.P.: An abstract architecture for rational agents. In: Proceedings of Knowledge Representation and Reasoning, pp. 439–449 (1992)

    Google Scholar 

  20. Yu, Q., Terzopoulos, D.: A decision network framework for the behavioral animation of virtual humans. In: Proceedings of Eurographics/ACM SIGGRAPH Symposium on Computer Animation 2007, San Diego, USA, pp. 119–128 (August 2007)

    Google Scholar 

  21. Rymill, S.J., Dodgson, N.A.: A psychologically-based simulation of human behaviour. In: Proceedings of Theory and Practice of Computer Graphics 2005, pp. 35–42 (2005)

    Google Scholar 

  22. Fridman, N., Kaminka, G.A.: Towards a cognitive model of crowd behavior based on social comparison theory. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, Vancouver, British Columbia, Canada, pp. 731–737 (July 2007)

    Google Scholar 

  23. Wolfram, S.: Theory and applications of Cellular Automata. World Press (1986)

    Google Scholar 

  24. Kirchner, A., Schadschneider, A.: Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A: Statistical Mechanics and its Applications 312(1-2), 260–276 (2002)

    Article  MATH  Google Scholar 

  25. Henein, C.M., White, T.: Macroscopic effects of microscopic forces between agents in crowd models. Physica A: Statistical Mechanics and its Applications 373, 694–712 (2007)

    Article  Google Scholar 

  26. Festinger, L.: A theory of social comparison processes. Human Relations, 117–140 (1954)

    Google Scholar 

  27. Pushkarev, B., Zupan, J.M.: Capacity of walkways. Transportation Research Record (538), 1–15 (1975)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, 430074, P.R. China

    Muzhou Xiong & Yunliang Chen

  2. School of Material Science and Chemistry, China University of Geosciences, Wuhan, 430074, P.R. China

    Hao Wang

  3. Chinese PLA Defense Information Academy, China

    Min Hu

Authors
  1. Muzhou Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunliang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Min Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, China

    Zhenhua Li  & Xiang Li  & 

  2. School of Computer Science and Engineering, The University of Aizu, Aizu, Japan

    Yong Liu

  3. School of Computer Science, China University of Geosciences, 430074, Wuhan, China

    Zhihua Cai

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xiong, M., Chen, Y., Wang, H., Hu, M. (2012). An Agent-Based Model for Simulating Human-Like Crowd in Dense Places. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34289-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34288-2

  • Online ISBN: 978-3-642-34289-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation