Combining Avoidance and Imitation to Improve Multi-agent Pedestrian Simulation

  • Luca Crociani
  • Giuseppe VizzariEmail author
  • Stefania Bandini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10037)


Simulation of pedestrian and crowd dynamics is a consolidated application of agent-based models but it still presents room for improvement. Wayfinding, for instance, is a fundamental task for the application of such models on complex environments, but it still requires both empirical evidences as well as models better reflecting them. In this paper, a novel model for the simulation of pedestrian wayfinding is discussed: it is aimed at providing general mechanisms that can be calibrated to reproduce specific empirical evidences like a proxemic tendency to avoid congestion, but also an imitation mechanism to stimulate the exploitation of longer but less congested paths explored by emerging leaders. A demonstration of the simulated dynamics on a large scale scenario will be illustrated in the paper and the achieved results will show the achieved improvements compared to a basic floor field Cellular Automata model.


Agent-based modeling and simulation Pedestrian simulation Wayfinding 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Luca Crociani
    • 1
  • Giuseppe Vizzari
    • 1
    Email author
  • Stefania Bandini
    • 1
    • 2
  1. 1.Complex Systems and Artificial Intelligence Research CentreUniversity of Milano-BicoccaMilanItaly
  2. 2.Researche Center for Advanced Science and TechnologyThe University of TokyoTokyoJapan

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