Skip to main content
SpringerLink
Log in

Experiment and analysis on microscopic characteristics of pedestrian movement in building bottleneck

  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

In this paper, evacuation experiments are carried out to study pedestrian movement behaviors in building bottleneck. An image processing method based on mean-shift algorithm is used to extract pedestrian movement trajectory. Based on the extracted trajectory, we analyze the microscopic movement characteristics of pedestrians such as lane formation, change of velocity and distance between two sequential pedestrians. A pedestrian lane is a group of pedestrians moving in a column. The lane formation is verified by the pedestrian trajectory and distribution of pedestrian’s lateral positions (x direction in the paper): lane number changes from one to two, three or even more with the increasing bottleneck width when pedestrians pass through the bottleneck. By analyzing the pedestrian movement behaviors in the same pedestrian lane, we find three typical movement modes in the bottleneck: time-lag acceleration, synchronous acceleration, and avoiding deceleration. Through analyzing the time intervals when successive pedestrians pass through the bottleneck, we find that most pedestrians adjust their velocities according to the distance to the forward pedestrians. Results also indicate that due to different cultures, pedestrians flux in China and Germany may have some differences besides their similarities.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Helbing D, Johansson A, Al-Abideen H Z. Dynamics of crowd disasters: An empirical study. Phys Rev E, 2007, 75: 0461091–97

    Article  Google Scholar 

  4. Tajima Y, Nagatani T. Scaling behavior of crowd flow outside a hall. Physica A, 2001, 292: 545–554

    Article  MATH  MathSciNet  Google Scholar 

  5. Tajima Y, Takimoto K, Nagatani T. Scaling of pedestrian channel flow with a bottleneck. Physica A, 2001, 294: 257–268

    Article  MATH  Google Scholar 

  6. Isobe M, Adachi T, Nagatani T. Experiment and simulation of pedestrian counter flow. Physica A, 2004, 336: 638–650

    Article  Google Scholar 

  7. Marconi S, Chopard B. A multiparticle lattice gas automata model for a crowd. Cellular Automata, 2002, 2493: 231–238

    Article  MathSciNet  Google Scholar 

  8. Song W G, Yu Y F, Wang B H, et al. Evacuation behaviors at exit in CA model with force essentials: A comparison with social force model. Physica A, 2006, 371: 658–666

    Article  Google Scholar 

  9. Fukui M, Ishibashi Y. Self-organized phase transitions in cellular automaton models for pedestrians. J Phys Soc Jpn, 1999, 68: 2861–2863

    Article  Google Scholar 

  10. Varas A, Cornejo M D, Mainemer D, et al. Cellular automaton model for evacuation process with obstacles. Physica A, 2007, 382: 631–642

    Article  Google Scholar 

  11. Song W G, Yu Y F, Fan W C, et al. A cellular automata evacuation model considering friction and repulsion. Sci China Ser E-Tech Sci, 2005, 48: 403–413

    Article  MATH  Google Scholar 

  12. Kirchner A, Schadschneider A. Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A, 2002, 312: 260–276

    Article  MATH  Google Scholar 

  13. Weng W G, Chen T, Yuan H Y, et al. Cellular automaton simulation of pedestrian counter flow with different walk velocities. Phys Rev E, 2006, 74: 0366102

    Article  Google Scholar 

  14. Yang L Z, Li J, Zhao D L, et al. A microcosmic discrete occupant evacuation model based on individual characteristics. Sci China Ser E-Tech Sci, 2004, 47: 608–615

    Article  Google Scholar 

  15. Couzin I D, Franks N R. Self-organized lane formation and optimized traffic flow in army ants. Proc Roy Soc London Ser B, 2003, 270: 139–146

    Article  Google Scholar 

  16. Hoogendoorn S P, Daamen W, Bovy P H L. Microscopic pedestrian traffic data collection and analysis by walking experiments: Behaviour at bottlenecks. Ped Evac Dyn, 2003: 89–100

  17. Gwynne S M V, Kuligowski E D, Kratchman J, et al. Questioning the linear relationship between doorway width and achievable flow rate. Fire Safety J, 2009, 44: 80–87

    Article  Google Scholar 

  18. Hoogendoorn S P, Daamen W. Pedestrian behavior at bottlenecks. Transport Sci, 2005, 39: 147–159

    Article  Google Scholar 

  19. Hoogendoorn S P, Daamen W, De Boer A, et al. Assessing passenger comfort and capacity bottlenecks in Dutch train stations. Transp Res Rec, 2007, 2002: 107–116

    Article  Google Scholar 

  20. Kretz T, Grunebohm A, Kaufman M, et al. Experimental study of pedestrian counterflow in a corridor. J Stat Mech-Theory Exp, 2006, 2006: P10001

    Article  Google Scholar 

  21. Kretz T, Wolki M, Schreckenberg M. Characterizing correlations of flow oscillations at bottlenecks. J Stat Mech-Theory Exp, 2006, 2006, 2006: P02005

    Article  Google Scholar 

  22. Liu X, Song W G, Zhang J. Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing. Physica A, 2009, 388: 2717–2726

    Article  Google Scholar 

  23. Nagai R, Fukamachi M, Nagatani T. Experiment and simulation for counterflow of people going on all fours. Physica A, 2005, 358: 516–528

    Article  Google Scholar 

  24. Helbing D. Traffic and related self-driven many-particle systems. Rev Mod Phys, 2001, 73: 1067–1141

    Article  Google Scholar 

  25. Helbing D, Molnar P, Farkas I J, et al. Self-organizing pedestrian movement. Environ Plan B-Plan Design, 2001, 28: 361–383

    Article  Google Scholar 

  26. Tajima Y, Takimoto K, Nagatani T. Pattern formation and jamming transition in pedestrian counter flow. Physica A, 2002, 313: 709–723

    Article  MATH  MathSciNet  Google Scholar 

  27. Burstedde C, Klauck K, Schadschneider A, et al. Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A, 2001, 295: 507–525

    Article  MATH  Google Scholar 

  28. Hoogendoorn S P, Daamen W, Bovy P H L. Experiments and theory of self-organization in pedestrian flow. Transp Res Board 85th Annu Meet, 2006. 06-1106

  29. Seyfried A, Passon O, Steffen B, et al. New insights into pedestrian flow through bottlenecks. Transport Sci, 2009, 43: 395–406

    Article  Google Scholar 

  30. Seyfried A, Steffen B, Winkens A, et al. Empirical data for pedestrian flow through bottlenecks. Traffic Granul Flow’ 07, 2009, 2009: 189–199

    Article  Google Scholar 

  31. Hartley R, Zisserman A. Multiple View Geometry in Computer Vision. Cambridge: Cambridge University Press, 2000

    MATH  Google Scholar 

  32. Fukunaga K, Hostertler L. The estimation of the gradient of a density function with application in pattern recognition. IEEE Trans Inform Theory, 1975, 21: 32–40

    Article  MATH  Google Scholar 

  33. Comaniciu D, Meer P. Mean shift mode seeking and clustering. IEEE Trans Patt Anal Mach Int, 2002, 17: 790–799

    Google Scholar 

  34. Comaniciu D, Ramesh V, Meer P. Kernel-based object tracking. IEEE Trans Patt Anal Mach Int, 2003, 25: 564–577

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, 230027, China

    Wei Tian, WeiGuo Song, Wei Lü & ZhiMing Fang

Authors
  1. Wei Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. WeiGuo Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei Lü
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. ZhiMing Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to WeiGuo Song.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tian, W., Song, W., Lü, W. et al. Experiment and analysis on microscopic characteristics of pedestrian movement in building bottleneck. Sci. China Technol. Sci. 54, 1730–1736 (2011). https://doi.org/10.1007/s11431-011-4425-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-011-4425-x

Keywords

Search

Navigation