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Title: Multi-agent Crowd Simulation in an Active Shooter Environment
In recent years there has been a sharp increase in active shooter events, but there has been no introduction of new technology or tactics capable of increasing preparedness and training for active shooter events. This has raised a major concern about the lack of tools that would allow robust predictions of realistic human movements and the lack of understanding about the interaction in designated simulation environments. It is impractical to carry out live experiments where thousands of people are evacuated from buildings designed for every possible emergency condition. There has been progress in understanding human movement, human motion synthesis, crowd dynamics, indoor environments, and their relationships with active shooter events, but challenges remain. This paper presents a virtual reality (VR) experimental setup for conducting virtual evacuation drills in response to extreme events and demonstrates the behavior of agents during an active shooter environment. The behavior of agents is implemented using behavior trees in the Unity gaming engine. The VR experimental setup can simulate human behavior during an active shooter event in a campus setting. A presence questionnaire (PQ) was used in the user study to evaluate the effectiveness and engagement of our active shooter environment. The results show that majority of users agreed that the sense of presence was increased when using the emergency response training environment for a building evacuation environment.  more » « less
Award ID(s):
2131116 2026412 1923986 2319752 2321539
NSF-PAR ID:
10335571
Author(s) / Creator(s):
Editor(s):
Chen, J.Y.C.
Date Published:
Journal Name:
Lecture notes in computer science
Volume:
13318
ISSN:
0302-9743
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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