Automation Type and Reliability Impact on Visual Automation Monitoring and Human Performance

ABSTRACT

We compared automation monitoring evolution of static or adaptive automation for four different reliability levels over 90 minutes. Previous studies have demonstrated degraded human performance when monitoring automation and that it is possible to mitigate this monitoring performance drop by using adaptive automation. We used the Open Multi-Attribute Task Battery to manipulate two type of automation (static automation without manual take-over sessions and adaptive automation with planned take-over sessions) and four levels of reliability. Participants performed three simultaneous tasks, one of which was automated. Our results suggest that a perfectly reliable or a totally unreliable automation led to different strategies by the participants in terms of visual allocation policy. Under static automation, the time spent looking at the automated task in the 0% reliability level increased over the duration of the experiment; however, the opposite was observed for the 100% reliability level. Although similar, the magnitude of this pattern of results was largely diminished under adaptive automation. For static automation, the reported data also showed a direct link between trust in automation and visual scanning strategies. The more the trust increased, the less the automated task was looked at.

Acknowledgments

This research was supported by grants from ANR (« Smart Planning » – ANR-16-CE26-0017).

Disclosure of potential conflicts of interest

The Authors declare that there is no conflict of interest.

Additional information

Notes on contributors

Eugénie Avril

Eugénie Avril obtained a PhD in cognitive ergonomics from the University of Toulouse in 2020. She received an MS in ergonomics from the INU Champollion, France, in 2017 and BA in psychology from the INU Champollion, France.

Julien Cegarra

Julien Cegarra is a full professor in the Department of Psychology at INU Champollion, France, and director of the Science of Cognition, Technology, and Ergonomics (ScoTE) Lab in Albi, France. He received his PhD in ergonomics from the University of Paris 8 in France in 2004.

Liên Wioland

Liên Wioland obtained a PhD in cognitive ergonomics from the University of Paris in 1997. From 1998 to 2002 she worked as a consultant in Human Factors in aviation and nuclear. In 2002 she joined INRS (French National Research and Safety Institute) in the research laboratory “psychology and ergonomics applied to prevention”.

Jordan Navarro

Jordan Navarro is a lecturer in psychology at the University of Lyon and has been appointed junior member of the Institut Universitaire de France. He obtained a PhD from the University of Nantes in 2008. His research interests focus on the human factors with advanced vehicle technologies and automation.