Fuzzy logic approach and sensitivity analysis for agent-based crowd injury modeling

Kuğu E., Li J., Mckenzie F. D.

SIMULATION, vol.90, no.3, pp.320-336, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 90 Issue: 3
  • Publication Date: 2014
  • Doi Number: 10.1177/0037549713518598
  • Journal Name: SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.320-336
  • Keywords: Agent-based simulation, fuzzy logic design, sensitivity analysis, crowd injury, SYSTEMS BIOLOGY, EXPLANATION, DYNAMICS, DESIGN
  • TED University Affiliated: No


A crowd is a group of people attending a public gathering with some joint purpose, such as protesting against the government or celebrating an event. In some countries, these kinds of activities are the only way to express public displeasure with their government. The government’s reactions to such activities may or may not be tolerant. For this reason, such situations must be eliminated by recognizing when and how they are likely to occur, and then providing guidelines to mitigate them. In urban areas, police and military forces use non-lethal weapons (NLWs), such as rubber bullets or clubs, to control a violent and destructive crowd. In order to estimate the results of this engagement, ensuring minimum injuries and reaching an optimal end state, simulating such actions in a virtual environment is necessary. In this work, a fuzzy logic-based crowd injury model for determining the physical effects of NLWs is proposed. Fuzzy logic concepts can be applied to a problem by using linguistic rules, which are determined by problem domain experts. A group of police and military officers were consulted for a set of injury model rules, and those rules were then included in the simulation platform. Sensitivity analysis has been conducted to analyze parameters in the model. As a proof of the concept, a prototype system was implemented using the Repast Simphony agent-based simulation toolkit. Simulation results illustrated the effectiveness of the simulation framework. © 2014, The Society for Modeling and Simulation International. All rights reserved.