The Effects of Multi-sensory Aerial Firefighting Training in Virtual Reality on Situational Awareness, Workload, and Presence

2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)(2020)

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摘要
Situational Awareness (SA) and managing workload are key factors in aerial firefighting, also known as Air Attack. Training for Air Attack is logistically challenging, risky, expensive, and difficult to practise in naturalistic settings. Simulation training in Virtual Reality (VR) has good potential to mitigate these challenges. This paper explored the application of VR Air Attack training with two multisensory immersive display types, an Oculus Rift CV1 VR Head Mounted Display (HMD) and a 270° Cylindrical Projection Display (CPD). Firefighters training to become Air Support Supervisors were recruited to participate in the study. SA, workload, and sense of presence in the virtual environment were measured. Qualitative data on the firefighters’ user experience and their subjective evaluation of the systems were also collected. This was to gain insights on the suitability of the two systems for Air Attack training, and whether the new systems were an improvement on earlier designs. The results show that the participants experienced a high level of SA, workload and presence in both conditions, with a direct comparison tentatively suggesting that the HMD system invoked slightly higher SA, greater overall presence and lower workload. The collected qualitative data suggest that the participating firefighters appreciated both systems for their realism, extensibility, cost-effectiveness, and accessibility. In particular participants noted that the virtual experience facilitated their understanding of the Air Attack role, and they recommended the use of virtual reality simulation training to supplement existing Air Attack training.
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关键词
Virtual Reality,Training,Assessment,User-Centered Design,Situated Learning,Aerial Firefighting,Human-centered computing,Visualization techniques,Visualization design,evaluation methods
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