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John Karasinski

Publications and source records attributed to John Karasinski.

Trade Space Analyses: Balancing Crew and Mission Design Parameters

In 2020, the Associate Administrator for Human Exploration and Operations and the Agency’s Federated Board requested an assessment to develop a methodology for trade space analysis comparing crew size for Mars missions against mission design parameters. The NASA Engineering and Safety Center (NESC) conducted an assessment to develop a methodology for systematic, repeatable trade space analysis for crew size and developed an initial set of human performance models and a list of candidate crew tasks for NASA’s first mission to Mars. This report contains the results of the NESC assessment.

Humans to Mars↗

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scheduling↗

Deep Space Human-Systems Research Recommendations for Future Human-Automation/Robotic Integration

Appropriate integration between automation and robotics systems and their human operators is essential for future space exploration. The Human Factors and Behavioral Performance Element of NASA’s Human Research Program requires a systematic understanding of the critical human-automation/robotic (HAR) integration, or HARI, design challenges for future space exploration. This document reports the results of a systematic assessment of the spaceflight-relevant HARI technologies and research topics addressing critical gaps in spaceflight-relevant HARI knowledge, and prioritizes research required for successful human performance and HAR integration. We reviewed relevant literature across the past ten years and interviewed ten subject matter experts to investigate the current state of HARI technology, challenges facing development, the state of HARI research across a wide range of fields, and opportunities for advancing the state of the art through directed research. This information was used to identify relevant HARI technologies and research topics, as well as factors to assess relative priority of HARI technologies. We worked with NASA stakeholders to weight the factors relevant to assessing HARI specific technologies. A multi-dimensional trade analysis was performed to objectively score HARI research topics and specific technologies to recommended investment priorities for NASA.

human-automation interaction↗

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗

The Impact of Delayed Communication on NASA’s Human-Systems Operations: Preliminary Results of a Systematic Review

Throughout the history of human spaceflight, NASA has relied on a team of ground-based experts on Earth to manage its missions, vehicles, and crews to ensure crew safety and mission success. However, as missions progress beyond low-Earth orbit (LEO), this paradigm of dependence on ground must evolve. Beyond LEO, in missions to the moon and Mars, crews will confront new challenges: limited evacuation options, reduced resupply capabilities, and significant communication delays that impede real-time support from experts on the ground. This reduction in ground support amplifies the likelihood that crews will be unable to adequately respond to unanticipated, safety-critical events. Understanding the scope of these risks and identifying effective countermeasures hinges on understanding the impact of communication delays on complex operations, especially in urgent, unforeseen events. Real-time communication currently provides the crew with continuous access to a large, extensively resourced ground team skilled in anomaly resolution. However, as communication delays grow, the need to transfer some responsibilities from ground experts to onboard crew becomes evident. NASA has been exploring this shift in operational responsibilities and its effectiveness in managing complex operations for decades. Nevertheless, a comprehensive understanding of the specific challenges posed by communication delays and the necessary countermeasures to mitigate them remains a gap. In this paper, we present an update on our systematic review of the literature on communication delays, the first in-depth review since 2013 (Rader et al.). We introduce a coding taxonomy to capture key constructs from papers of interest and discuss preliminary findings. These preliminary results suggest two significant research gaps: limited studies have been conducted 1) with lunar-like latencies and 2) on problem-solving strategies for the maximum latencies expected in Mars missions. We outline plans and propose recommendations to address these gaps through ongoing and future research.

human-systems integration↗

Crew Autonomy Through Self-Scheduling: Guidelines for Crew Scheduling Performance Envelope and Mitigation Strategies

NASA’s future long duration exploration missions (LDEMs) will encounter increasing communication transmission delays as they move farther from Earth-based ground stations. Because crews can no longer rely on real-time support from ground planners, they will have to self-schedule their own operational timelines effectively and efficiently. To enable this, our team develops Playbook, a mission planning and scheduling tool. Our research focuses on quantifying scheduling performance using Playbook to inform the design and development of future features aimed at streamlining timeline creation. We also aim to propose standards and guidelines for autonomous crews in LDEMs. This year, we discuss preliminary results from HERA Campaign 6.

self-scheduling↗

Information Systems for Crew-Led Operations Beyond Low-Earth Orbit

On past and present human space missions, the management of vehicle health and status has primarily been executed from Earth. Missions such as Apollo, Space Shuttle, and ISS have relied on a safety net of ground-based experts with access to real-time telemetry data, broad and deep systems expertise, and powerful analytical and computing capabilities. The ground team monitors and manages the vehicle’s health in real-time and responds quickly to critical situations and malfunctions. Ground operators also provide real-time oversight and verbal guidance to flight crew members, especially during complex procedure execution and high-risk activities like extra-vehicular activities. However, this operational paradigm, in place for 60 years, will not transfer to long duration exploration missions beyond low Earth orbit (LEO). Lunar and deep-space crewed missions will encounter delayed communications that prohibit real-time operational and medical support. Additionally, there will be infrequent resupply and a diminished capacity to evacuate or rescue crew members. A small crew must operate independently, managing the vehicle’s state, responding to time-critical events, and executing complex procedures, all without the safety net of real-time support.

data representation↗

Interface Consistency: Phase I Results & Phase II Status

Future exploration missions will rely on designing and developing vehicles and complex systems from within NASA and through multiple external commercial partners to meet mission goals. Despite existing consistency-related agency requirements, NASA’s approach to commercial spaceflight development encourages providers’ flexibility and innovation. This strategy is resulting in significant design diversity across Artemis vehicles. Design best practices and guidelines champion interface consistency to promote mental model development and knowledge transfer. However, research investigating the benefits of consistency is mixed, and little is known about its role in complex systems. Determining the level of risk that system diversity presents is difficult, as there is no established method for quantifying the degree of consistency within and across interfaces, nor is there information about the differential impacts of different types of inconsistency. Phase I of this project (Characterization and Measurement) served as a starting point to better understand the construct of consistency, its application, and the range of studies and methods for measuring it. The project team created a taxonomy of consistency to apply to interfaces as a framework to guide the development of tools to assess intersystem consistency. Checklist and cognitive walkthrough methods were developed for use by human factors (HF) and human-computer interaction (HCI) experts. The Intersystem Consistency Scale (ICS) was developed for interface evaluations with crew. A pilot study evaluated the methods’ ability to distinguish differences between Artemis-like prototype pairs exhibiting either high or low design consistency. In addition, click errors and time on task were collected within the ICS (crew-like) group. Results from our exploratory analysis and lessons learned from the pilot study will be discussed. The project team will also present the status of Phase II (Risk Assessment, Standards and Guidelines). This includes incorporating feedback to redesign the assessment tools, and inputs from displays and training Subject Matter Experts to update tasks and prototype designs. The team will present the risk assessment study design to identify the types and levels of inconsistency that pose the greatest risk to performance. Plans to apply these results toward agency standards and guideline recommendations will also be discussed.

Human-Computer Interaction↗

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

An Analysis of Extended Reality Mockups for Use in Verification: Phase 2

NASA commercial providers are increasing their use of Virtual Reality (VR) and Hybrid Reality (HR) technologies in their system development process. The use of these technologies, collectively referred to as Extended Reality (XR) technologies, has been limited to the development phase, but there have been requests to integrate VR and HR mockups into verifications. Verifications require, at minimum, a high-fidelity mockup for activities involving human participation (tests, demonstrations, inspections). HR technology shares many of the strengths but may not share some of the critical shortcomings of VR. Specifically, HR allows for integrating physical objects, such as a suit, which may be critical to evaluating a system. Adopting HR technology still has many of the same challenges as VR. Namely, there is little to no data about the validity of evaluations conducted with HR mockups, an established process, or criteria for evaluating the appropriateness of HR mockups. Because verifications are final and only need to happen once, HR mockups must be adequately vetted before being approved for use in verifications. Further hindering the adoption of these technologies is the lack of consensus on what constitutes a high-fidelity XR mockup. Even for physical mockups, there are guidelines and common criteria, but nothing has been formalized. Discussion about when an XR mockup can be used would be greatly helped by clearly defining what a high-fidelity XR mockup is and how it might be measured. The team will engage with relevant stakeholders to learn more about the benefits and challenges of adopting hybrid reality mockups for verification. The team will build upon work from Phase 1 by maturing a framework to guide decisions for evaluating XR mockups for use in verifications. The team will also conduct experimental studies to evaluate advantages and tradeoffs of hybrid/mixed reality relative to physical and virtual reality mockups. Finally, data from Phase 1 and Phase 2 will be synthesized into a set of best practices for developing and validating XR mockups for verification. We will highlight the work conducted to date in Phase 2. We will present the status of the XR for Verification Framework, a summary of best practices identified thus far, and give a synopsis of future work.

verification testing↗