Effect of Automation Transparency on Acceptance of Resolution Advisories in Air Traffic Control

Abstract

As air traffic controller workload is a bottleneck on air traffic growth, automation solutions have been proposed. This study investigates the effect of transparency on the acceptance of resolution advisories generated by an adaptive automation tool and the frustration experienced by controllers when using this tool.
Two different kinds of transparency were looked at. The first shows the variables the automation uses directly, while the second shows them only indirectly. Both incorporated a preview functionality, which allowed for comparison of the resolution advisory and the controller solution when the automation activated.
A human in the loop experiment featuring these different kinds of transparency was performed. The results show that there is no significant difference in acceptance of advisories, workload or frustration ratings obtained from the NASA-TLX between the different levels of transparency. However, the group using the direct form of transparency received more short-term collision alerts and the time that the automation was active was higher than for the group using the indirect transparency. No significant difference in controller trust in the automation was found.
In conclusion, there does not appear to be an influence of transparency on controller acceptance of resolution advisories, controller workload, controller frustration or controller trust in the automation. However, the experimenter noticed that most participants in the experiment did not use the information from the preview functionality to compare their solution to the resolution advisory. As they did not use the automation transparency to its full potential, further research on automation transparency is recommended in order to either confirm or dismiss the findings of this study