Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships. Gregor, A., Allison, R. S., & Heffner, K. In IEEE OCEANS Conference, pages 1-10, 2023.
Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships [link]-1  doi  abstract   bibtex   
Abstract—Consistent with the International Maritime Organisation's roadmap for regulating the operation of autonomous surface ships, most concepts of operations for crewed and uncrewed autonomous shipping rely on monitoring and operation from a Remote Control Centre (RCC). The successful execution of such activities requires that operators have adequate Situational Awareness (SA), while avoiding situations of information overload, and the right amount of, or calibrated, Trust in the system. In this study, we examined how operator SA and Trust were affected by different levels of Immersion of the human-machine interface. Simulated RCC interfaces were constructed for a scenario where an autonomous container ship traversed the arctic escorted by robotic aids. SA, Trust, and Motion Sickness (MS) were tracked over time. Different Virtual Reality (VR) technologies were used to represent three levels of Immersion: Non-Immersive VR (NVR), Semi-Immersive VR (SVR), and Immersive VR (IVR). The results illustrated various trade-offs – with NVR shown to be less taxing, SVR showing several potential benefits for SA, and IVR showing a strong relationship between Trust and SA accuracy, but increased MS. These results suggest that Immersion is an important factor in Situational Awareness and Trust in automation; future research should consider both the extent of Immersion, potential for MS, and the format of delivery (e.g. head-mounted displays versus immersive projection displays). Understanding these trade-offs between levels of Immersion is a requisite step for designing RCCs.
@inproceedings{Gregor:2023pz,
	abstract = {Abstract---Consistent with the International Maritime Organisation's
roadmap for regulating the operation of autonomous
surface ships, most concepts of operations for crewed and
uncrewed autonomous shipping rely on monitoring and operation
from a Remote Control Centre (RCC). The successful
execution of such activities requires that operators have adequate
Situational Awareness (SA), while avoiding situations of
information overload, and the right amount of, or calibrated,
Trust in the system. In this study, we examined how operator
SA and Trust were affected by different levels of Immersion of
the human-machine interface. Simulated RCC interfaces were
constructed for a scenario where an autonomous container ship
traversed the arctic escorted by robotic aids. SA, Trust, and
Motion Sickness (MS) were tracked over time. Different Virtual
Reality (VR) technologies were used to represent three levels
of Immersion: Non-Immersive VR (NVR), Semi-Immersive VR
(SVR), and Immersive VR (IVR). The results illustrated various
trade-offs -- with NVR shown to be less taxing, SVR showing
several potential benefits for SA, and IVR showing a strong
relationship between Trust and SA accuracy, but increased MS.
These results suggest that Immersion is an important factor in
Situational Awareness and Trust in automation; future research
should consider both the extent of Immersion, potential for MS,
and the format of delivery (e.g. head-mounted displays versus
immersive projection displays). Understanding these trade-offs
between levels of Immersion is a requisite step for designing
RCCs.},
	annote = {Limerick, 5-8 June 2023},
	author = {Gregor, A. and Allison, R. S. and Heffner, K.},
	booktitle = {IEEE OCEANS Conference},
	date-added = {2023-05-18 08:34:24 -0400},
	date-modified = {2023-10-14 14:56:29 -0400},
	doi = {10.1109/OCEANSLimerick52467.2023.10244249},
	keywords = {Augmented & Virtual Reality},
	pages = {1-10},
	title = {Exploring the Impact of Immersion on Situational Awareness and Trust in Remotely Monitored Maritime Autonomous Surface Ships},
	year = {2023},
	url-1 = {https://doi.org/10.1109/OCEANSLimerick52467.2023.10244249}}

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