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Computational and Applied Mathematics

, Volume 36, Issue 2, pp 1113–1141 | Cite as

A discrete mathematical model for the dynamics of a crowd of gazing pedestrians with and without an evolving environmental awareness

  • Annachiara Colombi
  • Marco Scianna
  • Alessandro Alaia
Article

Abstract

In this article, we present a microscopic-discrete mathematical model describing crowd dynamics in no panic conditions. More specifically, pedestrians are set to move in order to reach a target destination and their movement is influenced by both behavioral strategies and physical forces. Behavioral strategies include individual desire to remain sufficiently far from structural elements (walls and obstacles) and from other walkers, while physical forces account for interpersonal collisions. The resulting pedestrian behavior emerges therefore from non-local, anisotropic and short/long-range interactions. Relevant improvements of our mathematical model with respect to similar microscopic-discrete approaches present in the literature are: (i) each pedestrian has his/her own dynamic gazing direction, which is regarded to as an independent degree of freedom and (ii) each walker is allowed to take dynamic strategic decisions according to his/her environmental awareness, which increases due to new information acquired on the surrounding space through their visual region. The resulting mathematical modeling environment is then applied to specific scenarios that, although simplified, resemble real-word situations. In particular, we focus on pedestrian flow in two-dimensional buildings with several structural elements (i.e., corridors, divisors and columns, and exit doors). The noticeable heterogeneity of possible applications demonstrates the potential of our mathematical model in addressing different engineering problems, allowing for optimization issues as well.

Keywords

Crowd dynamics Evacuation Environmental awareness Gazing direction Social and physical forces 

Mathematics Subject Classification

90B20 91B10 92D25 68R01 34A30 

Notes

Acknowledgments

The authors want to thank Prof. Luigi Preziosi for fruitful discussions.

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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2016

Authors and Affiliations

  • Annachiara Colombi
    • 1
  • Marco Scianna
    • 1
  • Alessandro Alaia
    • 2
  1. 1.Department of Mathematical SciencesPolitecnico di TorinoTorinoItaly
  2. 2.Optimad EngineeringTorinoItaly

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