Potential measures for detecting trust changes

It is challenging to quantitatively measure a user´s trust in a robot system using traditional survey methods due to their invasiveness and tendency to disrupt the flow of operation. Therefore, we analyzed data from an existing experiment to identify measures which (1) have face validity for measuring trust and (2) align with the collected post-run trust measures. Two measures are promising as real-time indications of a drop in trust. The first is the time between the most recent warning and when the participant reduces the robot´s autonomy level. The second is the number of warnings prior to the reduction of the autonomy level.