Background - Long distance space exploration missions require the “right combination” of individuals to live and work productively for durations of well over 2 years. An extended timeline combined with unprecedented autonomy will also require the “right recombinations” of people on particular tasks and in response to mission events. This project leverages the CREWS agent-based model (ABM) developed and validated in NASA’s HERA analog to create a decision support tool, TEAMSTaR, that can be used by mission control and crew members to compose and effectively manage crews before or during the mission. Hypotheses - Our program will test two primary, but interrelated, hypotheses: (H1) Model predictions generated by TEAMSTaR accurately predict crew social relations, team cohesion, and team performance, (H2) Crew and mission control members make higher quality composition and scheduling decisions with the aid of TEAMSTaR and TEAMSTaR-generated guidance principles, than when making decisions without the aid of this decision support tool. Aims - The primary aims of the research are to a) refine the CREWS ABM looking at relevant input characteristics and their ability to predict team outcomes, b) develop and validate a Team Composition decision support system and user interface (e.g., TEAMSTaR) that aids crew and mission control decision making, c) identify and provide a rationale for key attributes, behaviors, emergent characteristics, and moderating and mediating factors, and d) validate TEAMSTaR using a software prototype in an extended duration, isolated and confined analog. Methods - This research will build on our CREWS ABM, which has been developed, refined, and initially validated with HERA C3-5 data, and is currently being updated using NEK 4-month data. To meet our research objectives, we will use previously collected data and lessons learned from NASA-funded projects that inform team Gaps 1 (key threats), Team Gap 2 (measures), and Team Gap 8 (Composition) to refine an extend our CREWS ABM. We will conduct virtual experiments to identify guiding principles that transcend a specific crew configuration to identify and provide a rationale for key attributes, behaviors, emergent characteristics, and moderating and mediating factors. We will develop and pilot test a working prototype of TEAMSTaR, a decision support tool. We will leverage relevant data previously collected in other analogs as well as collect new data in an analog environment to validate TEAMSTaR. Deliverables - (1) Report detailing best practices and guiding principles for composing space crews based on the CREWS ABM, providing evidence-based team composition and functioning algorithms. (2) Report summarizing CREWS model validation and TEAMSTaR evaluation data from ground-based analogs. (3) Report on model validation and efficacy identifying training requirements and use cases for the TEAMSTaR countermeasure. (4) Validation data sets for TEAMSTaR and source code prepared to be used for validation and verification in accordance with NASA Standard 7009a. (5) Report describing the validation of TEAMSTaR as a countermeasure for potential applications to support team functioning and performance when used as a decision support tool that could be used at multiple phases of a long-distance space exploration mission: pre-launch, transit, surface operations, and return transit. Significance - The research transitions foundational model validation and research conducted in project CREWS to create a validated tool useful in NASA operations to mitigate risks associated with high
|Effective start/end date||4/15/21 → 4/14/24|
- NASA Lyndon B. Johnson Space Center (80NSSC21K0925 P00006)
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