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Behavioral Human Crowds

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Crowd Dynamics, Volume 2

Abstract

This chapter provides an introduction to the contents of Gibelli (in Crowd Dynamics, Volume 2—Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, Birkhäuser, New York, 2020) and a general critical analysis on modeling, simulation, and control of human crowds with emphasis on research perspectives. The contents are organized in three parts: firstly, three key topics are stated which will be probably the focus of future research; Subsequently, the contents of Chaps. “Artificial Neural Networks for the Estimation of Pedestrian Interaction Forces–Mixed Traffic Simulation of Cars and Pedestrians for Transportation Policy Assessment” are summarized by setting them in the context of the aforementioned key research topics; finally, some promising research directions are presented and discussed.

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References

  1. G. Ajmone Marsan, N. Bellomo, L. Gibelli, Stochastic evolutionary differential games toward a systems theory of behavioral social dynamics. Math. Models Methods Appl. Sci. 26, 1051–1093 (2016)

    Article  MathSciNet  Google Scholar 

  2. G. Albi, M. Bongini, E. Cristiano, D. Kalise, Invisible control of self-organizing agents leaving unknown environments. SIAM J. Appl. Math. 76(4), 1683–1710 (2016)

    Article  MathSciNet  Google Scholar 

  3. G. Albi, E. Cristiani, L. Pareschi, D. Peri, Mathematical models and methods for crowd dynamics control, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 8 (Birkhäuser, New York, 2020)

    Google Scholar 

  4. B. Andreianov, C. Donatello, U. Razafison, M. D. Rosini, One-dimensional conservation laws with nonlocal point constraints on the flux, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018), pp. 103–135

    Google Scholar 

  5. B. Aylaj, N. Bellomo, L. Gibelli, A. Reali, On a unified multiscale vision of behavioral crowds. Math. Models Methods Appl. Sci. 30(1), 1–22 (2020)

    Article  MathSciNet  Google Scholar 

  6. R. Bailo, J.A. Carrillo, P. Degond, Pedestrian models based on rational behaviour, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018)

    Google Scholar 

  7. M.K. Banda, M. Herty, T. Trimborn, Recent developments in controlled crowd dynamics, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 7 (Birkhäuser, New York, 2020)

    Google Scholar 

  8. N. Bellomo, A. Bellouquid, On multiscale models of pedestrian crowds from mesoscopic to macroscopic. Commun. Math. Sci. 13(7), 1649–1664 (2015)

    Article  MathSciNet  Google Scholar 

  9. N. Bellomo, L. Gibelli, Toward a mathematical theory of behavioral-social dynamics for pedestrian crowds. Math. Models Methods Appl. Sci. 25(13), 2417–2437 (2015).

    Article  MathSciNet  Google Scholar 

  10. N. Bellomo, A. Bellouquid, D. Knopoff, From the micro-scale to collective crowd dynamics. Multiscale Model. Simul. 11, 943–963 (2013)

    Article  MathSciNet  Google Scholar 

  11. A.L. Bertozzi, J. Rosado, M.B. Short, L. Wang, Contagion shocks in one dimension. J. Stat. Phys. 158, 647–664 (2015)

    Article  MathSciNet  Google Scholar 

  12. N. Bellomo, D. Clarke, L. Gibelli, P. Townsend, B.J. Vreugdenhil, Human behaviours in evacuation crowd dynamics: from modeling to “big data” toward crisis management. Phys. Life Rev. 18, 1–21 (2016)

    Article  Google Scholar 

  13. N. Bellomo, L. Gibelli, N. Outada, On the interplay between behavioral dynamics and social interactions in human crowds. Kinetic Relat. Models 12, 397–409 (2019)

    Article  MathSciNet  Google Scholar 

  14. R. Borsche, A. Klar, F. Schneider, Numerical methods for mean-field and moment models for pedestrian flow, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 7 (Birkhäuser, New York, 2018)

    Google Scholar 

  15. A. Borzì The Fokker-Planck framework in the modeling of pedestrians’ motion, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 6 (Birkhäuser, New York, 2020)

    Google Scholar 

  16. M. Burger, P. Markowich, J.F. Pietschmann, Continuous limit of a crowd motion and herding model: analysis and numerical simulations. Kinetic Relat. Models 4(4), 1025–1047 (2011)

    Article  MathSciNet  Google Scholar 

  17. D. Burini, N. Chouhad, Hilbert method toward a multiscale analysis from kinetic to macroscopic models for active particles. Math. Models Methods Appl. Sci. 27, 1327–1353 (2017)

    Article  MathSciNet  Google Scholar 

  18. R.M. Colombo, M. Lecureux–Mercier, M. Garavello, Crowd dynamics through conservation laws, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 9 (Birkhäuser, New York, 2020)

    Google Scholar 

  19. M. Colangeli, A. Muntean, O. Richardson, T. Thieu, Modeling interactions between active and passive agents moving through heterogeneous environments, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018), pp. 211–258

    Google Scholar 

  20. A. Corbetta, A. Mountean, K. Vafayi, Parameter estimation of social forces in pedestrian dynamics models via probabilistic method. Math. Biosci. Eng. 12, 337–356 (2015)

    Article  MathSciNet  Google Scholar 

  21. A. Corbetta, L. Schilders, F. Toschi, High-statistics modeling of complex pedestrian avoidance scenarios, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 4 (Birkhäuser, New York, 2018)

    Google Scholar 

  22. E. Cristiani, F.S. Priuli, A. Tosin, Modeling rationality to control self-organization of crowds: an environmental approach. SIAM J. Appl. Math. 75(2), 605–629 (2015)

    Article  MathSciNet  Google Scholar 

  23. J.-M. Epstein, Modeling civil violence: an agent based computational approach. Proc. Natl. Acad. Sci. 99, 7243–7250 (2002)

    Article  Google Scholar 

  24. H. Fujii, H. Uchida, T. Yamada, S. Yoshimura, Mixed traffic simulation of cars and pedestrians for transportation policy assessment, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 2 (Birkhäuser, New York, 2020)

    Google Scholar 

  25. L. Gibelli, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2020)

    Google Scholar 

  26. L. Gibelli, N. Bellomo, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018), pp. 1–14

    Google Scholar 

  27. G.H. Goldsztein, Self-organization when pedestrians move in opposite directions. Multi-lane circular track model. Appl. Sci. 10, 563 (2020). https://doi.org/10.3390/app10020563

    Google Scholar 

  28. S. Göttlich, S. Knapp, Artificial neural networks for the estimation of pedestrian interaction forces, in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 3 (Birkhäuser, New York, 2020)

    Google Scholar 

  29. M. Haghani, M. Sarvi, Social dynamics in emergency evacuations: disentangling crowds attraction and repulsion effects. Phys. A 475, 24–34 (2017)

    Article  Google Scholar 

  30. D. Helbing, A. Johansson, Pedestrian Crowd and Evacuation Dynamics. Encyclopedia of Complexity and System Science (Springer, Berlin, 2009), pp. 6476–6495

    Book  Google Scholar 

  31. D. Helbing, P. Molnár, Social force model for pedestrian dynamics. Phys. Rev. E 51, 4282–4286 (1995)

    Article  Google Scholar 

  32. D. Helbing, A. Johansson, H.-Z. Al-Abideen, Dynamics of crowd disasters: an empirical study. Phys. Rev. E 75, 046109 (2007)

    Article  Google Scholar 

  33. D. Hilbert, Mathematical problems. Bullet. Am. Math. Soc. 8(10), 437–479 (1902)

    Article  MathSciNet  Google Scholar 

  34. M. Kinateder, T.D. Wirth, W.H. Warren, Crowd dynamics in virtual reality, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems, ed. by L. Gibelli, N. Bellomo. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018), pp. 15–36

    Google Scholar 

  35. B. Piccoli, F. Rossi, Measure-theoretic models for crowd dynamics, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology (Birkhäuser, New York, 2018)

    Google Scholar 

  36. E. Ronchi, D. Nilsson, Pedestrian movement in smoke: theory, data and modeling approaches, in Crowd Dynamics, Volume 1 - Theory, Models, and Safety Problems. Modeling and Simulation in Science, Engineering, and Technology, chap. 3 (Birkhäuser, New York, 2018)

    Google Scholar 

  37. A. Templeton, Inserire il titolo in Crowd Dynamics, Volume 2 - Theory, Models, and Safety Problems, ed. by L. Gibelli. Modeling and Simulation in Science, Engineering, and Technology, chap. 5 (Birkhäuser, New York, 2020)

    Google Scholar 

  38. H. Vermuyten, J. Belien, L. De Boeck, G. Reniers, T. Wauters, A review of optimisation models for pedestrian evacuation and design problems. Saf. Sci. 87, 167–178 (2016)

    Article  Google Scholar 

  39. L. Wang, M.B. Short, A.L. Bertozzi, Efficient numerical methods for multiscale crowd dynamics with emotional contagion. Math. Models Methods Appl. Sci. 27, 205–230 (2017)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Granada, Granada, Spain

    Nicola Bellomo

  2. IMATI CNR, Pavia, Italy

    Nicola Bellomo

  3. School of Engineering, University of Edinburgh, Edinburgh, UK

    Livio Gibelli

  4. University of Cordoba and CONICET, Cordoba, Argentina

    Damian Knopoff

Authors
  1. Nicola Bellomo
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  2. Livio Gibelli
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  3. Damian Knopoff
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Corresponding author

Correspondence to Livio Gibelli .

Editor information

Editors and Affiliations

  1. Institute for Multiscale Thermofluids, University of Edinburgh, Edinburgh, UK

    Livio Gibelli

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Bellomo, N., Gibelli, L., Knopoff, D. (2020). Behavioral Human Crowds. In: Gibelli, L. (eds) Crowd Dynamics, Volume 2. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-50450-2_1

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