Improving Emergency Response Training and Decision Making Using a Collaborative Virtual Reality Environment for Building Evacuation

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Abstract

Emergency response training is needed to remember and implement emergency operation plans (EOP) and procedures over long periods until an emergency occurs. There is also a need to develop an effective mechanism of teamwork under emergency conditions such as bomb blasts and active shooter events inside a building. One way to address these needs is to create a collaborative training module to study these emergencies and perform virtual evacuation drills. This paper presents a collaborative virtual reality (VR) environment for performing emergency response training for fire and smoke as well as for active shooter training scenarios. The collaborative environment is implemented in Unity 3D and is based on run, hide, and fight mode of emergency response. Our proposed collaborative virtual environment (CVE) is set up on the cloud and the participants can enter the VR environment as a policeman or as a civilian. We have used game creation as a metaphor for developing a CVE platform for conducting training exercises for different what-if scenarios in a safe and cost-effective manner. The novelty of our work lies in modeling behaviors of two kinds of agents in the environment: user-controlled agents and computer-controlled agents. The computer controlled agents are defined with preexisting rules of behaviors whereas the user controlled agents are autonomous agents that provide controls to the user to navigate in the CVE at their own pace. Our contribution lies in our approach to combine these two approaches of behavior to perform emergency response training for building evacuation.

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APA

Sharma, S. (2020). Improving Emergency Response Training and Decision Making Using a Collaborative Virtual Reality Environment for Building Evacuation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12428 LNCS, pp. 213–224). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59990-4_17

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