One of the daunting challenges astronauts face on long-duration exploration missions (LDEMs) is the need for the crew to perform tasks with greater autonomy than crewmembers face in low-Earth orbit (LEO). With increased distance, crewmembers face significant lag between communications with Mission Control Center (MCC). As a result of this lag, crewmembers will have more timely access to information regarding executing tasks and activities in response to disturbances than MCC. The lag in communication and success of LDEMs will require that crew be able to reschedule their own timeline without creating violations regarding the availability of resources, time, and the sequential requirements of activities.
In practice, planning and scheduling remain largely manual tasks due to limitations of the analytic and heuristic methods used to automate and optimize schedules using mathematical models. Human schedulers benefit from their flexible, adaptive, and creative capabilities. However, their success is often limited by the amount of information humans can simultaneously consider during scheduling. Developing human-computer interactive approaches may allow schedulers to mitigate these weaknesses, but many important questions remain to be answered. Time will be an extremely important factor in managing space exploration mission schedules and, yet, there is little research quantifying schedule performance using time as a criterion.
The goal of this Human Capabilities Assessments for Autonomous Missions (HCAAM) Virtual NASA Specialized Center of Research (VNSCOR) study is to quantify crew performance for self-scheduling using Playbook scheduling software according to the following aims.
1) Quantify crew performance envelop for the task of self-scheduling space flight operational plans,
2) Develop countermeasures to mitigate deficient crew self-scheduling performance,
3) Validate self-scheduling countermeasures by evaluating changes in crew performance with countermeasures in spaceflight analogs,
4) Recommend standards and guidelines appropriate for autonomous crews in LDEMs with regards to self-scheduling.
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This study will characterize the human performance envelope for the task of planning and scheduling (i.e. crew self-scheduling), develop countermeasures to mitigate adverse performance effects due to plan complexity, and inform performance standards and guidelines based on research results. The hypotheses driving this experiment are (1) planning and scheduling human performance will decrease as plan complexity increases and (2) countermeasures can ameliorate decreased self-scheduling performance, allowing crew to perform at an operationally relevant level. This experiment will require at least 36 human subjects for laboratory experiments (Aim 1) and 16 subjects for analog missions (Aim 3).
Aim 1 will establish a baseline characterization of crew self-scheduling performance across a series of controlled laboratory experiments. Novice human participants will complete short self-scheduling tasks using a bare-bone version of a scheduling tool. Measures that will be used to quantify self-scheduling performance will include efficiency, effectiveness, situational awareness, a trust rating relating to the scheduling software, and plan complexity. Controlled, lab-based human-in-the-loop experiments that manipulate plan complexity factors will be performed to determine crew performance.
Aim 2 will build on the information gathered during the course of Aim 1 by developing countermeasures to mitigate adverse effects on performance. Countermeasure development will include meetings with subject-matter experts (SMEs) such as Flight Controllers, Operations Planners and Capsule Communications (CAPCOMs), autonomous planning and scheduling researchers, long-duration mission planners and designers, and input and representation from the Astronaut Crew Office for the purpose of defining criteria for plan complexity. In addition to guiding countermeasure development, recommendations on performance limits resulting from these meetings will be folded into Aim 4, recommendations for NASA’s standards and guidelines for autonomous crew in LDEMs with regards to self-scheduling.
Aim 3 will evaluate the countermeasures produced by Aim 2 using analog missions and will require realistic, spaceflight operations scenarios driven by operational drivers as well as resource limitations. Each subject will be assigned a day to schedule and will complete a questionnaire after completing the scheduling activity. After the
scheduled timeline has been executed, all subjects will complete a questionnaire. A self-schedule team activity will also be conducted to allow the subjects to discuss the activities to be scheduled. Voice recorders will be used to document the team activity.
NASA has not yet characterized non-expert human performance for planning and scheduling, experimentally or otherwise. The researchers for this experiment hypothesize (1) planning and scheduling human performance will decrease as plan complexity increases and (2) countermeasures can ameliorate decreased self-scheduling performance, allowing crew to perform at an operationally relevant level. The results of this experiment will provide insight that can be generalized to (1) inform the development of planning, scheduling, and execution software tools for NASA, (2) improve roles that require planning and scheduling such as project planning, personnel scheduling, and operational management, and (3) develop mitigations to improve crew performance in complex planning tasks. The results will also provide the basis for crew self-scheduling standards and guidelines for LDEMs.