Presentation Title

Devising and Optimizing Crowd Control Strategies using Agent-Based Modeling and Simulation

Format of Presentation

Poster to be presented the Friday of the conference

Presenter Information

Ryan FicocelliFollow

Abstract

Sporting events can attract big crowds who cheer up their teams. Emotionally charged crowds can become, however, violent and disruptive, damaging and destroying public properties. Managing and controlling riotous crowds is an important responsibility for police officers to keep public order and safety. Devising and optimizing crowd control strategies is difficult without the knowledge of the scale of the crowd and their situations in advance. Thus, we created a 3D simulation to model to simulate a riot and the police response to the riot. It contains crowd agents (rioters), police agents, and transit systems. In this study, we focus on a specific crowd control strategy: pushing the crowd to the public transit. The police agents form police lines, which move towards targeted positions and push crowd agents towards the position as well. In order to optimally disperse crowds, the police lines move towards stops in the transit systems, pushing crowd agents to the vicinity of the public transit and containing the rioters there. By forcing the rioters into the area where public transit picks up passengers, the crowd would dissipate as members got on the transit to leave. The 2011 Vancouver Stanley Cup riot is used in our simulation as a case study. We compared the result of the actual crowd control of the event and that of our crowd control strategy of pushing. Our model and tool can be used for other sporting events at different locations and for devising different crowd control strategies.

Department

Computing Science

Faculty Advisor

Andrew Park

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Devising and Optimizing Crowd Control Strategies using Agent-Based Modeling and Simulation

Sporting events can attract big crowds who cheer up their teams. Emotionally charged crowds can become, however, violent and disruptive, damaging and destroying public properties. Managing and controlling riotous crowds is an important responsibility for police officers to keep public order and safety. Devising and optimizing crowd control strategies is difficult without the knowledge of the scale of the crowd and their situations in advance. Thus, we created a 3D simulation to model to simulate a riot and the police response to the riot. It contains crowd agents (rioters), police agents, and transit systems. In this study, we focus on a specific crowd control strategy: pushing the crowd to the public transit. The police agents form police lines, which move towards targeted positions and push crowd agents towards the position as well. In order to optimally disperse crowds, the police lines move towards stops in the transit systems, pushing crowd agents to the vicinity of the public transit and containing the rioters there. By forcing the rioters into the area where public transit picks up passengers, the crowd would dissipate as members got on the transit to leave. The 2011 Vancouver Stanley Cup riot is used in our simulation as a case study. We compared the result of the actual crowd control of the event and that of our crowd control strategy of pushing. Our model and tool can be used for other sporting events at different locations and for devising different crowd control strategies.