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Aerial firefighter radio communication performance in a virtual training system: radio communication disruptions simulated in VR for Air Attack Supervision

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Abstract

Communication disruptions are frequent in aerial firefighting. Information is more easily lost over multiple radio channels, busy with simultaneous conversations. Such a high bandwidth of information throughput creates mental overload. Further problems with hardware or radio signals being disrupted over long distances or by mountainous terrain make it difficult to coordinate firefighting efforts. This creates stressful conditions and requires certain expertise to manage effectively. An experiment was conducted which tested the effects of disrupting users communications equipment and measured their stress levels as well as communication performance. This research investigated how realistic communication disruptions have an effect on behavioural changes in communication frequency, as well as physiological stress by means of measuring heart rate variability (HRV). Broken radio transmissions created a greater degree of stress than background chatter alone. Experts could maintain a more stable HRV during disruptions than novices, which was calculated on the change in HRV during the experiment. From this, we deduce that experts have a better ability to manage stress. We also noted strategies employed by experts such as relaying to overcome the radio challenges, as opposed to novices who would not find a solution, effectively giving up.

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Acknowledgements

We would like to thank Richard McNamara a.k.a Mac and the Air Attack cohort from Fire and Emergency New Zealand (FENZ) for their valued time and input. We want to thank the Ngāi Tahu Research Centre as well as FENZ for providing funding for this research project.

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Correspondence to Rory M. S. Clifford.

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Clifford, R.M.S., Engelbrecht, H., Jung, S. et al. Aerial firefighter radio communication performance in a virtual training system: radio communication disruptions simulated in VR for Air Attack Supervision. Vis Comput 37, 63–76 (2021). https://doi.org/10.1007/s00371-020-01816-6

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