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Volume: 34 | Article ID: ERVR-299
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Immersive virtual reality training module for active shooter events
  DOI :  10.2352/EI.2022.34.12.ERVR-299  Published OnlineJanuary 2022
Abstract
Abstract

Active shooter events are not emergencies that can be reasonably anticipated. However, these events do occur more than we think, and there is a dire need for an effective evacuation plan that can increase the likelihood of saving lives and reducing casualties in the event of an active shooting incident. 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 environments. Clearly, 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 an immersive virtual reality (VR) experimental setup for conducting evacuation experiments and virtual evacuation drills in response to extreme events that impact the actions of occupants. We have presented two ways for controlling crowd behavior. First, by defining rules for agents or NPCs (Non-Player Characters). Second, by providing controls to the users as avatars or PCs (Player characters) to navigate in the VR environment as autonomous agents with a keyboard/ joystick along with an immersive VR headset in real time.The results will enable scientists and engineers to develop more realistic models of the systems they are designing, and to obtain greater insights into their eventual behavior, without having to build costly prototypes.

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  Cite this article 

Sharad Sharma, Sri Teja Bodempudi, "Immersive virtual reality training module for active shooter eventsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Engineering Reality of Virtual Reality,  2022,  pp 299-1 - 299-6,  https://doi.org/10.2352/EI.2022.34.12.ERVR-299

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