Advertisement

Empirical Investigation on Pedestrian Crowd Dynamics and Grouping

  • Andrea Gorrini
  • Stefania Bandini
  • Giuseppe Vizzari
Conference paper

Abstract

The definition and implementation of pedestrian simulation models requires empirical evidences, acquired by means of experiments and on-field observations, for sake of model calibration and validation. This paper describes an observation carried out in a urban commercial-touristic walkway (Vittorio Emanuele II Gallery, Milan, in collaboration with the Municipality of Milano). Although the analysis considered traditional metrics for describing pedestrian flow, such as the level of service, the main aim of this work was to quantify and characterize the presence, impact and behavior of groups in the observed population. In particular, we had confirmatory results on the frequency of groups in the observed situation, but we also achieved innovative results on trajectories and walking speeds: the walking path of individuals was 4 % longer than the average path of groups, but the average walking speed of group members was 37 % lower than the one of single pedestrians. Finally, a metric for characterizing group dispersion was defined and applied to the observed scenario: relatively large groups (size three and four) occupy more space in their movement when compared to couples. The achieved results represent useful empirical data for the calibration and validation of models for the simulation of pedestrians and crowd dynamics, but also for the development of automated techniques for data collection and analysis employing computer vision techniques.

Keywords

Spatial Cohesion Spatial Dispersion Pedestrian Flow Public Transport Service Highway Capacity Manual 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The survey was carried out thanks to the authorization of the Milano’s Municipality and complying the Italian legislation about the privacy of the people recorded within the pedestrian flows without their consent.

References

  1. 1.
    S. Bandini, A. Gorrini, G. Vizzari, Towards an integrated approach to crowd analysis and crowd synthesis: a case study and first results. Pattern Recognit. Lett. (2013). http://dx.doi.org/10.1016/j.patrec.2013.10.003
  2. 2.
    A. Baum, P. Paulus, Crowding, in Handbook of Environmental Psychology, vol. 1, ed. by D. Stokols, I. Altman (Wiley, New York, 1987), pp. 533–570Google Scholar
  3. 3.
    M. Costa, Interpersonal distances in group walking. J. Nonverbal Behav. 34(1), 15–26 (2010)CrossRefGoogle Scholar
  4. 4.
    W. Daamen, S. Hoogendoorn, Controlled experiments to derive walking behaviour. Eur. J. Transp. Infrastruct. Res. 3(1), 39–59 (2003)Google Scholar
  5. 5.
    M.L. Federici, A. Gorrini, L. Manenti, G. Vizzari, Data collection for modeling and simulation: case study at the university of milan-bicocca, in Cellular Automata (Springer, New York, 2012), pp. 699–708Google Scholar
  6. 6.
    J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, vol. 1 (Addison-Wesley, Harlow, 1999)Google Scholar
  7. 7.
    J.J. Fruin, Pedestrian Planning and Design (Metropolitan Association of Urban Designers and Environmental Planners, New York, 1971)Google Scholar
  8. 8.
    A. Gorrini, S. Bandini, M. Sarvi, C. Dias, N. Shiwakoti, An empirical study of crowd and pedestrian dynamics: the impact of different angle paths and grouping, in Transportation Research Board, 92nd Annual Meeting, Washington, D.C., 2013, p. 42Google Scholar
  9. 9.
    E. Hall, The Hidden Dimension (Doubleday, Garden City, 1966)Google Scholar
  10. 10.
    J.C.S. Jacques Junior, S.R. Musse, C.R. Jung, Crowd analysis using computer vision techniques. IEEE Signal Process. Mag. 27(5), 66–77 (2010)Google Scholar
  11. 11.
    G. Le Bon, The Crowd: A Study of the Popular Mind (Macmillan, London, 1897)Google Scholar
  12. 12.
    J.S. Milazzo II, N.M. Rouphail, J.E. Hummer, D.P. Allen, Quality of service for interrupted-flow pedestrian facilities in highway capacity manual 2000. Transp. Res. Rec.: J. Transp. Res. Board 1678(1), 25–31 (1999)Google Scholar
  13. 13.
    M. Moussaïd, N. Perozo, S. Garnier, D. Helbing, G. Theraulaz, The walking behaviour of pedestrian social groups and its impact on crowd dynamics. PloS one 5(4), e10047 (2010)Google Scholar
  14. 14.
    M. Schultz, C. Schulz, H. Fricke, Passenger dynamics at airport terminal environment, in Pedestrian and Evacuation Dynamics 2008, ed. by W.W.F. Klingsch, C. Rogsch, A. Schadschneider, M. Schreckenberg (Springer, Berlin/Heidelberg, 2010), pp. 381–396Google Scholar
  15. 15.
    J. Turner, Towards a cognitive redefinition of the social group. Curr. Psychol. Cogn. 1, 93–118 (1981)Google Scholar
  16. 16.
    G. Vizzari, L. Manenti, L. Crociani, Adaptive pedestrian behaviour for the preservation of group cohesion. Complex Adapt. Syst. Model. 1(7), 1–19 (2013)Google Scholar
  17. 17.
    A. Willis, N. Gjersoe, C. Havard, J. Kerridge, R. Kukla, Human movement behaviour in urban spaces: implications for the design and modelling of effective pedestrian environments. Environ. Plan. B Plan. Des. 31(6), 805–828 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andrea Gorrini
    • 1
  • Stefania Bandini
    • 2
  • Giuseppe Vizzari
    • 2
  1. 1.Information Society Ph.D. Program, Department of Sociology and Social ResearchUniversity of Milano-BicoccaMilanoItaly
  2. 2.Department of Informatics, Systems and Communications, Complex Systems and Artificial Intelligence Research CenterUniversity of Milano-BicoccaMilanoItaly

Personalised recommendations