Experimental Study of the Following Dynamics of Pedestrians

  • C. Appert-Rolland
  • A. Jelic
  • P. Degond
  • J. Fehrenbach
  • J. Hua
  • A. Cretual
  • R. Kulpa
  • A. Marin
  • A.-H. Olivier
  • S. Lemercier
  • J. Pettre
Conference paper

Abstract

We report some experimental study of the behavior of pedestrians when they follow each other. In the frame of the PEDIGREE project, trajectories of pedestrians walking along a one-dimensional path were tracked through a high-precision motion capture. Data analysis allowed to obtain the fundamental diagram at different scales. Two unexpected transitions in the way pedestrians follow each other have been evidenced. The interest of the experiment is to capture at the same time microscopic and macroscopic characteristics of the flow. Indeed, macroscopic structures such as stop-and-go waves can also be studied from the data. Eventually, a data-based following model has been proposed. Its calibration/validation can be performed both at the microscopic or macroscopic level. It is possible to extend the model to quasi-one-dimensional flows for the modeling of pedestrian flows in corridors.

Keywords

Pedestrian traffic Following behavior Microscopic model Fundamental diagram Modeling 

Notes

Acknowledgement

This work has been supported by the French’ Agence Nationale pour la Recherche (ANR)’ in the frame of the contract PEDIGREE (contract number ANR-08-SYSC-015-01). The project involves four research teams in Rennes (INRIA), Toulouse (IMT, CRCA), and Orsay (LPT). Experiments were organized and realized by the PEDIGREE partnership [25] at University Rennes 1, with the help of the laboratory M2S from Rennes 2.

A.J. acknowledges support from the RTRA Triangle de la physique (Project 2011-033T).

References

  1. 1.
    A. Schadschneider. Modelling of transport and traffic problems. In H. Umeo, S. Morishita, K. Nishinari, T. Komatsuzaki, and S. Bandini, editors, Cellular automata, Proceedings. Book Series: Lecture Notes in Computer Science, volume 5191, pages 22–31, 2008.Google Scholar
  2. 2.
    D. Helbing. Traffic and related self-driven many-particle systems. Reviews of Modern Physics, 73:1067–1141, 2001.CrossRefGoogle Scholar
  3. 3.
    D. Helbing and P. Molnár. Social force model for pedestrian dynamics. Phys. Rev. E, 51:4282–4286, 1995.CrossRefGoogle Scholar
  4. 4.
    C. Burstedde, K. Klauck, A. Schadschneider, and J. Zittartz. Simulation of pedestrian dynamics using a 2-dimensional cellular automaton. Physica A, 295:507–525, 2001.CrossRefMATHGoogle Scholar
  5. 5.
    J. Pettré, J. Ondřej, A.-H. Olivier, A. Cretual, and S. Donikian. Experiment-based modeling, simulation and validation of interactions between virtual walkers. In SCA ’09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pages 189–198. The Eurographics Association, 2009.Google Scholar
  6. 6.
    J. Ondrej, J. Pettré, A.-H. Olivier, and S. Donikian. A synthetic-vision based steering approach for crowd simulation. ACM Trans. Graphics, 29(123), 2010.Google Scholar
  7. 7.
    S. Paris, J. Pettré, and S. Donikian. Pedestrian reactive navigation for crowd simulation: a predictive approach. Computer Graphics Forum - Eurographics, 26(3):665–674, 2007.CrossRefGoogle Scholar
  8. 8.
    M. Moussaïd, D. Helbing, and G. Theraulaz. How simple rules determine pedestrian behavior and crowd disasters. Proc. Nat. Acad. Sci U.S.A., 108:6884–6888, 2011.CrossRefGoogle Scholar
  9. 9.
    A. Seyfried, B. Steffen, W. Klingsch, and M. Boltes. The fundamental diagram of pedestrian movement revisited. J. Stat. Mech., page P10002, 2005.Google Scholar
  10. 10.
    U. Chattaraj, A. Seyfried, and P. Chakroborty. Comparison of pedestrian fondamental diagram across cultures. Advances in Complex Systems, 12:393–405, 2009.CrossRefGoogle Scholar
  11. 11.
    A. Jelić, C. Appert-Rolland, S. Lemercier, and J. Pettré. Properties of pedestrians walking in line – fundamental diagrams. Phys. Rev. E, 85:036111, 2012.CrossRefGoogle Scholar
  12. 12.
    A. Jelić et al. Properties of pedestrians walking in line – stepping behavior. preprint, 2012.Google Scholar
  13. 13.
    S. Lemercier, A. Jelic, R. Kulpa, J. Hua, J. Fehrenbach, P. Degond, C. Appert-Rolland, S. Donikian, and J. Pettré. Realistic following behaviors for crowd simulation. To appear in Comput. Graphics Forum-Eurographics, 2012.Google Scholar
  14. 14.
    S. Lemercier, A. Jelic, J. Hua, J. Fehrenbach, P. Degond, C. Appert-Rolland, S. Donikian, and J. Pettré. Un modèle de suivi réaliste pour la simulation de foules. Revue Électronique Francophone d’Informatique Graphique, 5:67–76, 2011.Google Scholar
  15. 15.
    J. Hua, J. Fehrenbach, S. Lemercier, A. Jelic, C. Appert-Rolland, S. Donikian, J. Pettré, and P. Degond. Identification of a model of pedestrian following behavior. preprint, 2012.Google Scholar
  16. 16.
    S. Lemercier, M. Moreau, M. Moussaïd, G. Theraulaz, S. Donikian, and J. Pettré. Reconstructing motion capture data for human crowd study. Lecture Notes in Computer Science, 7060:365–376, 2011.CrossRefGoogle Scholar
  17. 17.
    J. Zhang, W. Klingsch, A. Schadschneider, and A. Seyfried. Transitions in pedestrian fundamental diagrams of straight corridors and t-junctions. J. Stat. Mech., page P06004, 2011.Google Scholar
  18. 18.
    W. Daamen and S.P. Hoogendoorn. Experimental research of pedestrian walking behavior. Transportation Research Record, 1828:20–30, 2003.CrossRefGoogle Scholar
  19. 19.
    A. Seyfried, B. Steffen, W. Klingsch, T. Lippert, and M. Boltes. Steps toward the fundamental diagram - empirical results and modelling. In N. Waldau, P. Gattermann, H. Knoflacher, and M. Schreckenberg, editors, Pedestrian and Evacuation Dynamics 2005. Berlin, Springer, 2007.Google Scholar
  20. 20.
    A. Aw, A. Klar, T. Materne, and M. Rascle. Derivation of continuum traffic flow models from microscopic Follow-the-Leader models. SIAM Journal on Applied Mathematics, 63:259–278, 2002.CrossRefMATHMathSciNetGoogle Scholar
  21. 21.
    A. Seyfried, B. Steffen, and T. Lippert. Basics of modelling the pedestrian flow. Physica A, 368:232–238, 2006.CrossRefGoogle Scholar
  22. 22.
    M. Chraibi, A. Seyfried, and A. Schadschneider. Generalized centrifugal-force model for pedestrian dynamics. Phys. Rev. E, 82:046111, 2010.CrossRefGoogle Scholar
  23. 23.
    M. Moussaïd, E. Guillot, M. Moreau, J. Fehrenbach, O. Chabiron, S. Lemercier, J. Pettré, C. Appert-Rolland, P. Degond, and G. Theraulaz. Traffic instabilities in self-organized pedestrian crowds. PLoS Computational Biology, 8:1002442, 2012.CrossRefGoogle Scholar
  24. 24.
    J. Zhang, W. Klingsch, A. Schadschneider, and A. Seyfried. Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram. J. Stat. Mech., page P02002, 2012.Google Scholar
  25. 25.
    More information can be found at http://www.pedigree-project.info.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • C. Appert-Rolland
    • 1
    • 2
  • A. Jelic
    • 1
    • 2
  • P. Degond
    • 3
    • 4
  • J. Fehrenbach
    • 3
    • 4
  • J. Hua
    • 3
    • 4
    • 5
  • A. Cretual
    • 6
  • R. Kulpa
    • 6
  • A. Marin
    • 6
  • A.-H. Olivier
    • 7
  • S. Lemercier
    • 7
  • J. Pettre
    • 7
  1. 1.Laboratory of Theoretical Physics UMR 8627CNRSORSAY CedexFrance
  2. 2.Laboratory of Theoretical PhysicsUniversity Paris-SudORSAY CedexFrance
  3. 3.Institut de Mathématiques de ToulouseUniversité de Toulouse; UPS, INSA, UT1, UTMToulouseFrance
  4. 4.Institut de Mathématiques de Toulouse UMR 5219CNRSToulouseFrance
  5. 5.Laboratory Jean KuntzmannUniversité de Grenoble, CNRSGrenoble CedexFrance
  6. 6.M2S – MimeTIC – University Rennes 2RennesFrance
  7. 7.INRIA Rennes – Bretagne AtlantiqueRennesFrance

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