Skip to main content
Log in

Crowd simulation: applying mobile grids to the social force model

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

The social force model (SF) is able to reproduce many emergent phenomena observed in real crowds. Unfortunately, in some situations, such as low density environments, SF may produce counterintuitive results where the trajectories simulated look more like particles than to real people. We modify the SF model through the use of a mobile grid to allow the simulated pedestrians to change the direction of their desired velocity at reasonable times, thus avoiding nearby blocked or crowded areas smoothly. Our experiments focus on qualitative behavior, and verify that our model produces the desired trajectories of the pedestrians, achieving softer and more coherent trajectories when compared to the pure SF model solution. Like SF, our model reproduces the “faster-is-slower” and the arching underlying the clogging effects. Finally, we examine the occupation rates of the space when pedestrians were submitted to narrowed corridors and observe the “edge effect.”

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Goldenstein, S., Large, E., Metaxas, D.: Non-linear dynamical system approach to behavior modeling. Vis. Comput. 15(7), 349–364 (1999)

    Article  Google Scholar 

  2. Goldenstein, S., Karavelas, M., Metaxas, D., Guibas, L., Aaron, E., Goswami, A.: Scalable nonlinear dynamical systems for agent steering and crowd simulation. Comput. Graph. 25(6), 983–998 (2001)

    Article  Google Scholar 

  3. Guo, R., Huang, H.: A mobile lattice gas model for simulating pedestrian evacuation. Physica A, Stat. Mech. Appl. 387(2–3), 580–586 (2008)

    Article  Google Scholar 

  4. Helbing, D., Molnár, P.: Social force model for pedestrian dynamics. Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 51(5), 4282–4286 (1995)

    Article  Google Scholar 

  5. Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407(6803), 487–490 (2000)

    Article  Google Scholar 

  6. Helbing, D., Johansson, A., Al-Abideen, H.: The dynamics of crowd disasters: An empirical study. Phys. Rev. E, Stat. Nonlin. Soft Matter Phys. 75(4) (2007)

  7. Henderson, L.F.: The statistics of crowd fluids. Nature 229(5284), 381–383 (1971)

    Article  Google Scholar 

  8. Huang, L., Wong, S.C., Zhang, M., Shu, C., Lam, W.H.K.: Revisiting Hughes’ dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm. Transp. Res., Part B, Methodol. 43(1), 127–141 (2009)

    Article  Google Scholar 

  9. Hughes, R.L.: A continuum theory for the flow of pedestrians. Transp. Res., Part B, Methodol. 36(6), 507–535 (2002)

    Article  Google Scholar 

  10. Kapadia, M., Singh, S., Hewlett, W., Faloutsos, P.: Egocentric affordance fields in pedestrian steering. In: Proceedings of the 2009 Symposium on Interactive 3D Graphics and Games, pp. 215–223 (2009)

    Chapter  Google Scholar 

  11. Lerner, A., Fitusi, E., Chrysanthou, Y., Cohen-Or, D.: Fitting behaviors to pedestrian simulations. In: Eurographics Symposium on Computer Animation, pp. 199–208 (2009)

    Google Scholar 

  12. Muramatsu, M., Irie, T., Nagatani, T.: Jamming transition in pedestrian counter flow. Physica A, Stat. Theor. Phys. 267(3–4), 487–498 (1999)

    Google Scholar 

  13. Musse, S., Thalmann, D.: Hierarchical model for real time simulation of virtual human crowds. IEEE Trans. Vis. Comput. Graph. 7, 152–164 (2001)

    Article  Google Scholar 

  14. Musse, S., Jung, C., Jacques, J. Jr., Braun, A.: Using computer vision to simulate the motion of virtual agents: Research articles. Comput. Animat. Virtual Worlds 18(2), 83–93 (2007)

    Article  Google Scholar 

  15. Perez, G.J., Tapang, G., Lim, M., Saloma, C.: Streaming, disruptive interference and power-law behavior in the exit dynamics of confined pedestrians. Physica A, Stat. Mech. Appl. 312(3–4), 609–618 (2002)

    Article  MATH  Google Scholar 

  16. Reynolds, C.: Flocks, herds and schools: A distributed behavioral model. SIGGRAPH 21(4), 25–34 (1987)

    Article  Google Scholar 

  17. Shao, W., Terzopoulos, D.: Autonomous pedestrians. In: Eurographics Symposium on Computer Animation, pp. 19–28 (2005)

    Google Scholar 

  18. Singh, S., Kapadia, M., Faloutsos, P., Reinman, G.: Steerbench: A benchmark suite for evaluating steering behaviors. Comput. Animat. Virtual Worlds 20(5–6), 533–548 (2009)

    Article  Google Scholar 

  19. Still, G.: Crowd dynamics. Ph.D. thesis, Mathematics Department, Warwick University (2000)

  20. Tajima, Y., Nagatani, T.: Scaling behavior of crowd flow outside a hall. Physica A, Stat. Mech. Appl. 292(1–4), 545–554 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  21. Treuille, A., Cooper, S., Popović, Z.: Continuum crowds. In: SIGGRAPH, pp. 1160–1168 (2006)

    Google Scholar 

  22. Tu, X., Terzopoulos, D.: Artificial fishes: Physics, locomotion, perception, behavior. In: SIGGRAPH, pp. 43–50 (1994)

    Google Scholar 

  23. Varas, A., Cornejo, M., Mainemer, D., Toledo, B., Rogan, J., Munoz, V., Valdivia, J.: Cellular automaton model for evacuation process with obstacles. Physica A, Stat. Mech. Appl. 382(2), 631–642 (2007)

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank CNPq, CAPES, and FAPESP for the financial support. We also express our gratitude to Dirk Helbing, Illés Farkas, and Tamás Vicsek for kindly providing us with their source code.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Priscila Saboia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Saboia, P., Goldenstein, S. Crowd simulation: applying mobile grids to the social force model. Vis Comput 28, 1039–1048 (2012). https://doi.org/10.1007/s00371-012-0731-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-012-0731-y

Keywords

Navigation