Objective We define human–autonomy teaming and offer a synthesis of the existing empirical research on the topic. Specifically, we identify the research environments, dependent variables, themes representing the key findings, and critical future research directions. Background Whereas a burgeoning literature on high-performance teamwork identifies the factors critical to success, much less is known about how human–autonomy teams (HATs) achieve success. Human–autonomy teamwork involves humans working interdependently toward a common goal along with autonomous agents. Autonomous agents involve a degree of self-government and self-directed behavior (agency), and autonomous agents take on a unique role or set of tasks and work interdependently with human team members to achieve a shared objective. Method We searched the literature on human–autonomy teaming. To meet our criteria for inclusion, the paper needed to involve empirical research and meet our definition of human–autonomy teaming. We found 76 articles that met our criteria for inclusion. Results We report on research environments and we find that the key independent variables involve autonomous agent characteristics, team composition, task characteristics, human individual differences, training, and communication. We identify themes for each of these and discuss the future research needs. Conclusion There are areas where research findings are clear and consistent, but there are many opportunities for future research. Particularly important will be research that identifies mechanisms linking team input to team output variables.

Objective Three different team configurations are compared with the goal of better understanding human-autonomy teaming (HAT). Background Although an extensive literature on human-automation interaction exists, much less is known about HAT in which humans and autonomous agents interact as coordinated units. Further research must be conducted to better understand how all-human teams compare to HAT. Methods In an unmanned aerial system (UAS) context, a comparison was made among three types of three-member teams: (1) synthetic teams in which the pilot role is assigned to a synthetic teammate, (2) control teams in which the pilot was an inexperienced human, and (3) experimenter teams in which an experimenter served as an experienced pilot. Ten of each type of team participated. Measures of team performance, target processing efficiency, team situation awareness, and team verbal behaviors were analyzed. Results Synthetic teams performed as well at the mission level as control (all human) teams but processed targets less efficiently. Experimenter teams performed better across all other measures compared to control and synthetic teams. Conclusion Though there is potential for a synthetic agent to function as a full-fledged teammate, further advances in autonomy are needed to improve team-level dynamics in HAT teams. Application This research contributes to our understanding of how to make autonomy a good team player.

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