Simulating Urban pedestrian crowds of different cultures

Gal A. Kaminka, Natalie Fridman

Research output: Contribution to journalArticlepeer-review

Abstract

Models of crowd dynamics are critically important for urban planning and management. They support analysis, facilitate qualitative and quantitative predictions, and synthesize behaviors for simulations. One promising approach to crowd modeling relies on micro-level agent-based simulations, where the interactions of simulated individual agents in the crowd result in macro-level crowd dynamics which are the object of study. This article reports on an agent-based model of urban pedestrian crowds, where culture is explicitly modeled. We extend an established agent-based social agent model, inspired by social psychology, to account for individual cultural attributes discussed in social science literature. We then embed the model in a simulation of pedestrians and explore the resulting macro-level crowd behaviors, such as pedestrian flow, lane changes rate, and so on. We validate the model by quantitatively comparing the simulation results to the pedestrian dynamics in movies of human crowds in five different countries: Iraq, Israel, England, Canada, and France. We conclude that the model can faithfully replicate urban pedestrians in different cultures. Encouraged by these results, we explore simulations of mixed-culture pedestrian crowds.

Original languageEnglish
Article number27
JournalACM Transactions on Intelligent Systems and Technology
Volume9
Issue number3
DOIs
StatePublished - Feb 2018

Keywords

  • Agent-based simulation
  • Crowd modeling
  • Culture modeling
  • Pedestrian
  • Social simulation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Artificial Intelligence

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