Exploring Team Error Management in Human Autonomy Teams During Automation Errors

Human Autonomy Teams (HATs) have been studied and many factors can influence HAT performance. However, how HATs manage team errors has yet to be understood. This paper explores how HATs manage team errors, specifically after automation errors and after receiving different forms of team training, using previously collected data. Three-member teams of two humans and one AI teammate were studied, completing reconnaissance tasks using Remotely Piloted Aircraft Systems (RPAS). The findings indicate that training methods may influence the effectiveness of team error management, and earlier detection and communication of the errors does not necessarily mean a more efficient error management process. Future research is needed to better understand this process within HATs.