A Multi-agent Simulation for the Mass School Shootings

TL;DR

This paper presents a multi-agent simulation model to evaluate the effectiveness of gunshot detection systems in reducing casualties and improving evacuation during school shootings, demonstrating significant safety improvements in simulated scenarios.

Contribution

The study introduces a novel multi-agent simulation framework to assess mitigation strategies for school shootings, specifically evaluating gunshot detection systems' impact on safety outcomes.

Findings

Evacuation rates increased from 16.6% to 66.6%.

Casualty rates decreased from 24.0% to 12.2%.

Simulation results suggest gunshot detection systems can significantly improve safety.

Abstract

The increasing frequency of mass school shootings in the United States has been raised as a critical concern. Active shooters kill innocent students and educators in schools. These tragic events highlight the urgent need for effective strategies to minimize casualties. This study aims to address the challenge of simulating and assessing potential mitigation measures by developing a multi-agent simulation model. Our model is designed to estimate casualty rates and evacuation efficiency during active shooter scenarios within school buildings. The simulation evaluates the impact of a gun detection system on safety outcomes. By simulating school shooting incidents with and without this system, we observe a significant improvement in evacuation rates, which increased from 16.6% to 66.6%. Furthermore, the Gun Detection System reduced the average casualty rate from 24.0% to 12.2% within a period of six minutes, based on a simulated environment with 100 students. We conducted a total of 48 simulations across three different floor layouts, varying the number of students and time intervals to assess the system's adaptability. We anticipate that the research will provide a starting point for demonstrating that a gunshot detection system can significantly improve both evacuation rates and casualty reduction.