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Modelling human perception processes in pedestrian dynamics: a hybrid approach.

A Colombi1, M Scianna1

  • 1Department of Mathematical Sciences , Politecnico di Torino , Corso Duca degli Abruzzi 24, 10129 Torino, Italy.

Royal Society Open Science
|April 14, 2017
PubMed
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This study introduces a hybrid model for crowd dynamics, enhancing pedestrian movement simulations by considering subjective perception of others. The model improves understanding of pedestrian behavior and social forces.

Area of Science:

  • Mathematical modeling
  • Complex systems
  • Social physics

Background:

  • Crowd dynamics are often modeled using discrete pedestrian simulations.
  • Existing models like the Helbing model incorporate physical and social forces.
  • Pedestrian perception of others significantly influences movement behavior.

Purpose of the Study:

  • To present a novel hybrid mathematical model for crowd dynamics.
  • To investigate the impact of pedestrian perception (objective vs. subjective) on movement.
  • To validate the model against real-world experiments and simulations.

Main Methods:

  • Developed a hybrid discrete model based on Helbing-like principles.
  • Incorporated physical forces (collisions) and social forces (territorial effect).
Keywords:
human perceptionlocalized versus distributed perceptionpedestrian dynamicsrepulsive behavioursocial force model

Related Experiment Videos

  • Differentiated pedestrian repulsive behavior based on objective or subjective perception of neighbors.

    • Main Results:

    • The model successfully reproduces a real-world experiment designed to derive its hypotheses.
    • Numerical simulations reveal distinct pedestrian path patterns based on perception types.
    • Analytical investigations provide mathematical validation for simulation outcomes.

    Conclusions:

    • The proposed hybrid model offers a more nuanced representation of crowd dynamics.
    • Pedestrian perception significantly influences individual movement and group behavior.
    • The model provides a robust framework for studying pedestrian flow and social interactions.