Human-Autonomy Teaming (HAT) requirements and characteristics for future aerospace operations have been developed through the synthesis of a new literature review of empirical HAT studies and two previously conducted case students in Single Pilot Operations (SPO) (Tokadlı et al., 2021a) and beyond low-Earth orbit (LEO) space operations (Tokadlı and Dorneich, 2018). Current automated systems, while highly capable, do not yet approach the level of sophistication needed to be considered true teammates. The requirements and characteristics developed in this work enumerate the capabilities needed to support HAT concepts in future aerospace operations, and serve as a roadmap of the types of capabilities that need to be developed to get closer to team-like systems.

While developing advanced intelligent systems, it is often challenging to predict and define the capabilities needed for future concepts of operation. This is particularly challenging when designing for future concepts of operation, which are often ill-defined and still under development. Thus, it is often the case that work does not touch on the specifics of a concept of operations but instead focuses more on the human interaction and perception of autonomous systems in teaming settings. Therefore, this work focuses on synthesizing the HAT requirements in the aerospace domain for two future concepts of operations: SPO in commercial air transportation and Space Operations beyond LEO. The common requirements and characteristics for HAT of this work provide some initial guidance on how to develop autonomous systems with the necessary capabilities to function as an autonomous teammate in future aerospace operations and address many human factors issues of increasingly autonomous systems working in a tightly coupled manner with humans.

This work aims to develop a set of high-level system feature and behavior requirements for HAT design in future aerospace operations to identify the capabilities and functions needed for an autonomous system to fully participate in HAT as a teammate. Two case studies drew upon a review of the empirical literature in HAT using a systematic approach to develop a future concept of operation and related requirements. In addition, a review of recent literature on HAT evaluation studies was performed, focused on work published after the case studies were completed. The results of the two case studies and the empirical literature review were synthesized to define common HAT characteristics and requirements for future aerospace operations (see Figure 1).

The previous studies investigated Single Pilot Operations/Reduced Pilot Operations (SPO/RCO) in commercial aviation (see details of case study from Tokadlı et al. (2021a); Tokadlı et al. (2021b)) and space operations beyond LEO (see details of case study from Tokadlı and Dorneich. (2018); Tokadlı and Dorneich, (2022)) as future aerospace operations with HAT concepts. These case studies were selected because they represented differences in the integration of an autonomous system in the team composition. While SPO/RCO reduces the number of pilots in the cockpit from two to one and add an autonomous system to replace the eliminated pilot, space operations beyond LEO either adds an autonomous teammate without removing any human astronaut or replace one astronaut with an autonomous system. This section summarizes each case study by providing concept of operations, case study analysis and findings through the experiments.

Several research areas are relevant to developing a human-autonomy team to support new concepts of operations that include increasingly autonomous systems. The emerging literature in human-autonomy teaming establishes the current state of the science on the characteristics and needs of human and autonomous teammates.

The case studies were each initiated with a thorough literature review to develop the concept of operations, extrapolate domain knowledge models to future operations, and inform the evaluations. For this paper, more recent work has been reviewed here to incorporate new findings in the evaluation of HAT systems in order to inform a synthesis of the two case studies to develop HAT characteristics and requirements for HAT in aerospace systems. This section summarizes insights gained from recent literature on HAT evaluation studies and whether they can be used as evidence for supporting human-autonomy teaming requirements. Table 1 summarizes 12 papers relevant to the scope of the review.

When reviewing the work, several themes emerged: teaming skills and characteristics, autonomous teammate capabilities, training, and human-like aspects (see Table 2).

With the introduction of autonomous systems into human teaming, the roles, tasks, and interactions should be designed to support the engagement, mode awareness, vigilance, and awareness of teammate(s) (Neis, 2020). Zhang et al. (2021) found that human pilots preferred to have the final authority on the autonomous system and be able to intervene whenever it is necessary to keep the flight safe. Similar perspectives were gathered from participants in the SPO Case Study from both interviews and the summative evaluation (Tokadlı et al., 2021b). Even though humans want to remain in control and charge, monitoring each other’s HAT performance can also help support coordination and identify possible errors. For example, a human pilot monitors the autonomous system to detect errors due to potential sensor failures, while the autonomous system can monitor pilot progress through procedures (Zhang et al., 2021).

Essential all-human teaming skills such as coordination, communication, and cooperation should be maintained for HAT, according to recent empirical HAT studies. By allocating some tasks to the existing automation systems and autonomous teammates, human teammate(s) have more time and fewer distractions to focus on essential information (Faulhaber et al., 2022).

Well-defined procedures and role allocations support cooperation between pilots. By adapting best practices from dual-pilot operations to SPO, a single pilot and autonomous teammate should fluidly hand over tasks to each other depending on the situation (Zhang et al., 2021). Some example functions that can be allocated between an autonomous system and humans include checking displayed information, updating logs, comparing against predictions, checking engine health, planning escape routes, checking weather/atmosphere conditions, maneuvering, docking/undocking, system maintenance, assigned activity support, payload assistance, crew assistance, data analysis, and interpretation (Karasinski et al., 2020; Neis, 2020). While allocating tasks between humans and autonomous systems dynamically during operations, autonomous systems should provide human teammates with information on their capabilities (Ulusoy and Reisman, 2022). For example, this can be supported with a procedure categorized by autonomous system capabilities. The autonomous system should support collision avoidance, assist in situation awareness, and notify when capabilities are lost or diminished (Weiss et al., 2022).

Communication is another key teaming skill. If the autonomous system can explain its actions and reasoning, this can build trust between teammates (Le Vie et al., 2021; Zhang et al., 2021; Faulhaber et al., 2022; Faulhaber et al., 2022). In some cases, the participants preferred explanations that help prevent and mitigate anomalies and provide actionable information to make informed decisions (Barkouki et al., 2023).

Pilots mentioned several ways that they missed the ability of autonomous systems to communicate in ways similar to human-human dialogs (Zhang et al., 2021). Communication between humans and autonomous systems must allow the system to understand human intentions, think ahead, and react appropriately to complex and changing situations (Zhang et al., 2021). This communication skill should be bi-directional (Shively et al., 2017). In addition to verbal communication, the autonomous system should be able to engage in non-verbal communication to provide contextual information using social cues (Chan, et al., 2021). Cue-based communication can support the pilot’s perception of the autonomous system’s presence. Some studies recommended that the autonomous system should have human-like behaviors and anthropomorphic features (Zhang et al., 2021; Ulusoy and Reisman, 2022). Similarly, the evaluations of case studies showed that the human teammates’ perception of teammate-likeness increased with an embodied autonomous teammate that provided cues of actions taken (Tokadlı et al., 2021a; Tokadlı and Dorneich, 2022).

Training varies for emerging autonomous systems and can focus on areas such as system capabilities or interactions. Current training processes should be adjusted for HAT concepts to enable human crew members to perform newly allocated tasks and new procedures (Faulhaber et al., 2022). There might be a need for novel training techniques to support crews. For example, just-in-time training might be provided for critical tasks when the crew is not able to receive mission control support (Karasinski et al., 2020). Training duration may increase (Alvarez, 2020). Insufficient training in HAT may result in over- and under-trust issues (Karasinski et al., 2020).

This work defines characteristics as the distinctive features, skills, or qualities that identify the system in its work context. Characteristics are used in this work to describe what makes an autonomous system a teammate in the work context of HAT. Several characteristics emerged from the results of the two case studies and the review of recent literature on HAT empirical studies. Areas of commonality in the development of HAT systems included team roles, expected teammate capabilities, autonomous teammate embodiment, interaction paradigms, and communication modalities. This section proposes the generalizable characteristics recommended for future aerospace operations in HAT concepts.

In this work, a requirement defines a system or service’s necessary attribute, capability, functionality, or quality (The MITRE Corporation, 2014). Based on the guidance on Turk (2006), the requirements were developed to follow the suggested format (e.g., use of “shall” statements) to provide what is needed rather than how to accomplish them. Since the future concept of operations are still ill-defined, these requirements serve as a reference starting point for systems and human factors engineers or researchers to define what is needed to truly achieve teaming between human and autonomous system. Thus, they can further define the detailed low-level system/sub-system requirements based on the concept of operations in the future. Comparing and synthesizing HAT requirements from the case studies and the recent empirical literature review resulted in 36 requirements (see Table 3). The requirements were categorized into themes: teaming, capability, allocation, interface, and training.

Teaming-01 . Teammates’ roles, tasks, and interactions should be strategized to maintain an optimal level of teammate engagement and situation awareness (Neis, 2020). As an example from aviation, crew resource management (CRM) methods developed for dual-pilot operations and would need to be re-designed for the mixed, flexible, and distributed HAT within SPO (Johnson, et al., 2012; Comerford et al., 2013; Faulhaber et al., 2022). CRM focuses on improving teamwork through communication and interactions between the flight crew members and ground personnel and how teams can reduce errors and make safer decisions (Salas et al., 2006; National Business Aviation Association, 2023). The autonomous teammate should follow current CRM best practices (Matessa et al., 2017).

Teaming-02; Capability-01 . In HAT, a backup strategy should be identified to manage failures, errors, and incapacitation cases. In the space mission beyond LEO case study, there is a strong need for a backup system when the collaborative work between the crews on Earth and in space is interrupted (Tokadlı and Dorneich, 2018). For example, in one case study, human teammates expected an autonomous teammate to monitor crew health conditions and performance and detect and notify them if a teammate becomes incapacitated. In the case of a human teammate’s incapacitation, the autonomous teammate should initiate a backup strategy and take over tasks. If the autonomous teammate cannot perform any allocated task(s), it should assist in allocating the task to another human.

Teaming-03; Capability-04, 05, 07, and 09 . To provide sufficient support while performing safety-critical tasks, ground and flight/space crews should be allowed to communicate as freely as needed (Johnson, et al., 2012; Neogi et al., 2016). Like all-human teaming, communication in HAT is a necessary and effective tool to improve team performance while exchanging information and monitoring each other’s actions (Shively et al., 2017; Faulhaber et al., 2022). Effective communication can support human teammates’ trust, including autonomous agents explaining their actions or decision-making process (Le Vie et al., 2021; Zhang et al., 2021; Faulhaber et al., 2022). Autonomous systems should be able to engage their teammates with non-verbal communication to provide contextual information using social cues (Chan, et al., 2021). However, HAT may necessitate additional communications requirements for safety-critical tasks, including potential monitoring and risk management requirements to make real-time decisions (Comerford, et al., 2013; Neogi et al., 2016). Technology must support the coordination between the air and the ground. For example, the autonomous teammate in the SPO cockpit should be capable of communicating vehicle-to-vehicle and ground-to-vehicle to send and receive brief safety messages and execute lost link procedures if voice communication cannot be established (Goodrich et al., 2016).

Teaming-04; Capability-07 . Humans and autonomous systems should monitor each other to identify possible failures (Zhang et al., 2021). An autonomous teammate could monitor the pilot’s capabilities and health to detect pilot incapacitation and intervene to safely land the aircraft (Comerford et al., 2013; Matessa et al., 2017). The human pilot should still be required to monitor the autonomous system to deal with errors due to potential sensor failures (Zhang et al., 2021). Alternatively, in some off-nominal or contingency situations, the autonomous teammate may not always be capable of performing all of its tasks. If necessary, a pilot should be alerted to take over the tasks (Matessa et al., 2017).

Teaming-05. The guidance of autonomous teammates could be categorized as crew, task, and maintenance assistance. To assist the crew, the autonomous teammate could monitor the crew, vehicle, environment, and mission states (ref. Capability-05 and Teaming-04) and provide updates and notify them if any action is necessary (ref. Capability-10). In both case studies, one teammate needs to read the step-by-step checklist tasks aloud to guide the other teammate during execution. Today’s space operations heavily rely on real-time guidance and support from the Mission Control Center on Earth. For example, this might include task-specific guidance during extravehicular activities (Clancey, 2003; McCann et al., 2005) or resolution support during off-nominal and emergency conditions (Love and Reagan, 2013; Fischer and Mosier, 2014). In space missions beyond LEO, the autonomous teammate could execute extravehicular activities or provide step-by-step action guidance to the human astronaut to accomplish the activity since Mission Control cannot perform this duty. For example, Mission Control supports maintenance issues by guiding the space crew to properly and quickly locate the issues in the space station structures, based on Mission Control’s ability to monitor the entire system’s health. With the communication delay, this can be delegated to an autonomous teammate as well as providing information regarding situation severity and mitigations.

Capability-02; Allocation-01 to 06. The interaction paradigm should shift towards more dialog-based coordination and back-and-forth delegation decisions between human and autonomous teammates to maintain coordination in HAT. Allowing flexible coordination can be possible with a dynamic function/role allocation strategy. Allocating some tasks to the autonomous teammate (e.g., flap settings, landing gear settings) can allow human teammate(s) more time to focus on essential information and create fewer distractions (Faulhaber et al., 2022). For example, a single pilot and autonomous system should fluidly hand over tasks to each other depending on the situation (Zhang et al., 2021). Like a human teammate, an autonomous teammate could dynamically modify task assignments between the human and autonomous teammates as conditions change (Johnson, 2010; Comerford et al., 2013; Neogi et al., 2016; Ho et al., 2017). However, allocating the tasks should be done with an awareness of each teammate’s capabilities and limitations (Ulusoy and Reisman, 2022). For example, a procedure should be categorized by autonomous system capabilities. Knowing what tasks the autonomous teammate can perform helps humans make better decisions, specifically when delegating tasks in emergencies.

Capability-11; Interface-03, 04, 06, and 07. A HAT should be able to manage resources and the impacts of unexpected events based on understanding the big picture (Chan et al., 2021). This necessitates that the autonomous teammate be capable of prioritizing tasks and plans during the mission. For example, the single pilot and autonomous teammate need to monitor and coordinate priorities (Comerford, et al., 2013). Some required SPO tasks of the autonomous teammate may include checklists, task reminders, challenge-and-response protocols, and recall of information or instructions provided by the single pilot, ATC personnel, or ground support (Matessa et al., 2017).

Capability-14. Checklists and procedures enable human teammates to form expectations of how the systems should respond at each step and to understand when the system does not respond as expected (Zhang et al., 2021). When the checklist or procedure task(s) does not help resolve the situation, the autonomous system should detect it and propose alternatives based on its system assessment.

Train-01 to 04 . Current operational and crew training strategies should be adjusted to suit the HAT concept to help human teammates efficiently prepare for missions with the autonomous teammate(s). This adjustment includes considering training duration, experience level (novice vs. expert), and training methods. Insufficient training in HAT may result in trust issues (Karasinski et al., 2020). Pilots indicated they wanted to be aware of an autonomous teammate’s experience and knowledge level to calibrate better their expectations of its performance (Tokadlı et al., 2021a). Training programs of HAT could be supported with various steps. For example, a certification can indicate the human teammate’s expertise level (and maybe the autonomous system’s experience level). In SPO, novice pilots will lose the opportunity they had in dual-pilot operations to train with expert pilots. This type of apprenticeship training would need to be provided differently in SPO. In space operations, in-mission training might be provided for critical tasks when the crew cannot receive mission control support or has not encountered such a situation (Karasinski et al., 2020).

HAT is a promising concept to support complex operations; its integration requires human teammates to develop and maintain a shared mental model, situation awareness, mode awareness, and collaboration with the autonomous teammate. Conversely, it is less clear what functions and capabilities make an autonomous system truly a teammate. This paper detailed the capabilities and characteristics of HAT system in future aerospace concepts of operations to identify the gaps between the capabilities of today’s automation and what is needed in HAT. A systematic analysis of the empirical HAT studies in the literature and two previous case studies of future operations were synthesized to enumerate the common capabilities that are needed for autonomous system in teaming settings. Much of the current HAT literature has focused on the “perception of teammate-likeness” (Hugues et al., 2016; Haring et al., 2021; Tokadlı and Dorneich, 2022). In contrast, the goal of this work was to be concrete about the functions and capabilities that are needed for autonomous system to truly be considered and accepted as a teammate. Although rapidly developing with advances in sensors, artificial intelligence, and interaction technology, today’s automated systems do not yet approach the capabilities needed to realize HAT. The functions and capabilities identify the areas that need more development.

The HAT requirements and characteristics can inform future autonomous system development in aerospace operations to get closer to teammate-like systems. However, more work is necessary to verify and validate these requirements for HAT development and test them in realistic mission environments. Future work should focus on areas such as an autonomous teammate’s potential learning ability, core teaming processes (e.g., conflict, coaching, cognition), physical embodiment and social interactions. In more complex concept of operations, the social interaction skills with and without embodiment of the autonomous system in HAT should be examined to better understand the human perception of teammate likeness.

HAT is an important concept in many domains. This work focused only on the aerospace domain and was restricted to two use cases. Future work will be done to expand analysis to incorporate more use cases within aerospace (e.g., urban air mobility), and extend to other domains (e.g., healthcare, manufacturing).