An agent-based model and computational framework for counter-terrorism and public safety based on swarm intelligencea
1 Institute for Canadian Urban Research Studies (ICURS), Simon Fraser University, Burnaby, BC, Canada and Thompson Rivers University, Kamploops, BC, Canada
2 Trinity Western University, , Langley, BC, Canada
3 Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS) Centre, Simon Fraser University, Burnaby, BC, Canada
Security Informatics 2012, 1:23 doi:10.1186/2190-8532-1-23Published: 23 December 2012
Public safety has been a great concern in recent years as terrorism occurs everywhere. When a public event is held in an urban environment like Olympic games or soccer games, it is important to keep the public safe and at the same time, to have a specific plan to control and rescue the public in the case of a terrorist attack. In order to better position public safety in communities against potential threats, it is of utmost importance to identify existing gaps, define priorities and focus on developing approaches to address those.
In this paper, we present a system which aims at providing a decision support, threats response planning and risk assessment. Threats can be in the form of Chemical, Biological, Radiological, Nuclear and Explosive (CBRNE) weapons and technologies. In order to assess and manage possible risks of such attacks, we have developed a computational framework of simulating terrorist attacks, crowd behaviors, and police or safety guards’ rescue missions. The characteristics of crowd behaviors are modeled based on social science research findings and our own virtual environment experiments with real human participants. Based on gender and age, a person has a different behavioral characteristic. Our framework is based on swarm intelligence and agent-based modeling, which allows us to create a large number of people with specific behavioral characteristics. Different test scenarios can be created by importing or creating 3D urban environments and putting certain terrorist attacks (such as bombs or toxic gas) on specific locations and time-lines.