Human-Autonomy Teams: The Case of Remote Operators and Automated Driving Systems

Autonomous functions, systems, and operations are expected to play a significant role in a number of industries, including energy, process, and transportation. In these, human operator teams frequently monitor, supervise, and intervene in the system's operations, acting as a safety barrier in the event of emergencies. As the Level of Automation of these systems increases, the need to study the Human-Autonomy Team's (HAT's) performance becomes fundamental. Recent developments in Automated Driving Systems (ADS) deployed for passenger transport services highlight the need to revisit assumptions about the role of remote operators performing driving assistance and emergency management tasks. While human factors research has explored the implications of human-system interactions in ADS contexts for drivers, the focus on HAT dynamics is still incipient, particularly in remote operations. This work draws from remote control operations in nuclear, oil & gas, and maritime industries, aiming to model fundamental aspects of HATs in remote ADS operations. Thus, instead of only considering human-system interaction schemes, team performance models such as the Information, Decision, and Action in Crew (IDAC) context can be applied to study the developing HAT dynamics. This work explores the applicability of Performance Shaping Factors (PSFs) used in Human Reliability Analysis (HRA) models, identifying potential factors influencing the performance of both human and automated agents in remote ADS operations, focusing on the relationship, tasks, and challenges remote operators face when interacting with vehicles equipped with advanced ADS.

Keywords: Automated driving systems, Remote driving assistance, Performance shaping factors.