Lessons From MOL: Crew Autonomy, Performance, and Psychological Demands
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Williams, Thomas J.↗
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Crew Health & Performance 101
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Kevin MacNeill↗
Decision Making in Action: Applying Research to Practice
The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.
Orasanu, Judith↗
Decision Making in Action: Applying Research to Practice
The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.
Orasanu, Judith↗
Decision Making in Action
The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.
Orasanu, Judith↗
Decision Making in the Airplane
The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.
Orasanu, Judith↗
Effects of Long-Duration Space Flight on Training Retention and Transfer
The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members cognitive performance in space can be predicted from the performance of crew members on the ground.
Barshi, Immanuel↗
Effects of Long-Duration Space Flight on Training Retention and Transfer
The space environment imposes on the astronaut crew significant physiological, psycho-social, and cognitive loads that can not be replicated on the ground. These loads likely impact crew performance. To date, no systematic data collection has taken place to understand the effects of such loads on crew members’ ability to retain trained knowledge and skills, and to transfer such knowledge and skills to novel situations. The research described here was originally requested by HRP management to be the first such study to systematically collect data on the effects of long duration space flight on training retention and transfer. Because current theories of retention and transfer are based on results obtained in university laboratories using undergraduate students as research participants, and because crew time in space is very expensive, this study was designed to compare the performance of 4 groups of subjects: crew members in space, crew members on the ground, crew-like subjects, and university undergraduate students. Results from the ground-phase of the study reported here demonstrate that crew members’ performance under cognitive load can not be predicted from the performance of university undergraduate students. It is still an open question the extent to which crew members’ cognitive performance in space can be predicted from the performance of crew members on the ground.
training↗
Preliminary results from the evaluation of Cockpit Resource Management training - Performance ratings of flightcrews
The first data from the NASA/University of Texas Crew Performance project on the behavior of flightcrews with and without formal training in Cockpit Resource Management (CRM) is reported. Expert observers made detailed ratings of 15 components of crew behavior in both line operations and in full mission simulations. The results indicate that such training in crew coordination concepts increases the percentage of crews rated as above average in performance and decreases the percentage rated as below average. The data also show high and unexpected degrees of variations in rated performance among crews flying different aircraft within the same organization. It was also found that the specific behaviors that triggered observer ratings of above or below average performance differed markedly between organizations. Characteristics of experts' ratings and future research needs are also discussed.
Helmreich, Robert L.↗
Crew behavior and performance in space analog environments
The objectives and the current status of the Crew Factors research program conducted at NASA-Ames Research Center are reviewed. The principal objectives of the program are to determine the effects of a broad class of input variables on crew performance and to provide guidance with respect to the design and management of crews assigned to future space missions. A wide range of research environments are utilized, including controlled experimental settings, high fidelity full mission simulator facilities, and fully operational field environments. Key group processes are identified, and preliminary data are presented on the effect of crew size, type, and structure on team performance.
Kanki, Barbara G.↗
Navigational demands of low-level helicopter flight
The present study was designed to assess the verbal references to map, terrain, direction, and position, that navigators and pilots communicate during a simulated low-level flight. Two-person crews were asked to communicate normally while negotiating six short flight missions that varied widely in regard to map-terrain characteristics. Half of the crews performed the exercises with fixed, north-up maps and the other half used movable maps that were adjusted to maintain a track-up correspondence to the flight route. An analysis was performed to compare differences in crew communication patterns between map orientations, characteristics, and navigation tasks. The results showed differences in the frequency of communication across categories for map characteristics but not for map orientations or tasks. A difference in the proportion of communications between pilot and navigator occurred when crew were lost. Pilots communicated more than navigators when crews were lost and the reverse was true when crews were not lost. The results support and extend findings from a distance error performance analysis performed on the same flight missions.
Delzell, Susanne↗
Shared Problem Models and Crew Decision Making
The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.
Orasanu, Judith↗
Crew Health and Performance (CHP) Technology Roadmaps
The Environmental Control and Life Support System (ECLSS) – Crew Health and Performance (CHP) Systems Capability Leadership Team (SCLT) is a community of practice (not a funded program) sponsored by Headquarters to develop, retain, and infuse the ECLSS and CHP capabilities necessary to enable the human exploration of the Moon and Mars through the integration and empowerment of experts across NASA, other government agencies, commercial industry, and academia. The goals of the SCLT are as follows: Use the Architecture Definition Document use cases and functions to identify gaps in NASA’s current technological capabilities to meet Agency objectives and develop strategies and roadmaps for closing such gaps Make technical/strategic recommendations on ECLSS and CHP technology development efforts and investments for PPBE, acquisition strategies, and leveraging NASA’s critical capabilities Establish key performance parameters and participate in key program and project reviews Maintain cognizance of relevant ECLSS and CHP national and international technology activities in government, industry, and academia, specifically, emerging innovations and technologies, trends, and opportunities Coordinate with commercial and international partners to identify areas of mutual interest and cooperation Support future mission and system architecture studies for human exploration This document is intended to be a comprehensive overview of the strategic development plans, or Roadmaps, of key technologies and capabilities identified by the SCLT. Each Roadmap is organized by Capability Gap as the gap name and number appears in STARPort, follows a fiscal year timeline, and displays any additional information on milestones, decision points, or important details on the right-hand side of the page. The Roadmaps should be used to facilitate discussion, decision making, and planning for programs and development projects, but are not expected to accurately depict the details and statuses of the projects and tasks appearing within the plans.
Human Health and Performance↗
STS-114: Discovery Day 3 Mission Status Briefing
Paul Hill, STS-114 Lead Shuttle Flight Director and John Shannon, Space Shuttle Flight Operations and Integration Manager are seen in this STS-114 flight day three Mission Status Briefing. Hill expresses that the Discovery Orbiter is performing beautifully and that STS-114 crew performed a picture perfect rendezvous. He also shows a video of the Rendezvous Pitch Maneuver (RPM) where Commander Eileen Collins slowly flips Discovery in a circle to give the Expedition 11 crew a view of Discovery's heat resistant tiles. He talks about the removal of the Multi-Purpose Logistics Module (MPLM) from Discovery's payload bay using the ISS Robotic Arm. Shannon discusses two objectives that his team is fulfilling on this mission. They include: 1) Understanding the health of Space Shuttle Discovery; and 2) Assessing the performance of the External Tank. Questions from the news media pertaining to the life expectancy of the Space Shuttle Discovery, battery lifetime on the wing leading edge impact sensors, foam loss, PAL ramps, and the safety of the Space Shuttle Discovery are addressed.
Source record↗
Artemis III and IV Crew Health and Performance System Model Development
To maintain Crew Health and Performance (CHP) during an Artemis mission, the NASA Human Research Program (HRP) and Exploration Medical Capabilities (ExMC) element recognize the challenge that many different vehicles, habitats, and operational groups must come together to develop and implement cross program capabilities. To address this challenge, the ExMC team created the prototype 2023 Artemis CHP System Model to analyze how human system requirements are implemented throughout an Artemis mission and help understand the effects of changing an individual vehicle or habitat requirement on a full mission. Since presenting this work at the 2024 HRP Investigators’ Workshop, ExMC has continued this effort, now called the Artemis III and IV CHP System Model, to better support its operational end users within the NASA Human Health and Performance Directorate (HHPD) workforce. In this presentation, we will recapitulate how visualizing requirements and their relationships using a Model-Based Systems Engineering approach (MBSE) serves to improve understanding of an Artemis mission’s CHP capabilities along with discussion on updates made to the model to increase accessibility for users within HHPD so that it may be used in the development of cross program CHP capabilities at NASA.
Crew Health and Performance↗
NASA Exercise Physiology and Countermeasures Project Overview
Efficient exercise countermeasures are necessary to offset or minimize spaceflight-induced deconditioning and to maximize crew performance of mission tasks. These countermeasure protocols should use the fewest crew and vehicle resources. NASA s Exercise Physiology and Countermeasures (ExPC) Project works to identify, collect, interpret, and summarize evidence that results in effective exercise countermeasure protocols which protect crew health and performance during International Space Station (ISS) and future exploration-class missions. The ExPC and NASA s Human Research Program are sponsoring multiple studies to evaluate and improve the efficacy of spaceflight exercise countermeasures. First, the Project will measure maximal aerobic capacity (VO2max) during cycle ergometry before, during, and after ISS missions. Second, the Project is sponsoring an evaluation of a new prototype harness that offers improved comfort and increased loading during treadmill operations. Third, the Functional Tasks Test protocol will map performance of anticipated lunar mission tasks with physiologic systems before and after short and long-duration spaceflight, to target system contributions and the tailoring of exercise protocols to maximize performance. In addition to these studies that are actively enrolling crewmember participants, the ExPC is planning new studies that include an evaluation of a higher-intensity/lower-volume exercise countermeasure protocol aboard the ISS using the Advanced Resistive Exercise Device and second-generation treadmill, studies that evaluate bone loading during spaceflight exercise, and ground-based studies that focus on fitness for duty standards required to complete lunar mission tasks and for which exercise protocols need to protect. Summaries of these current and future studies and strategies will be provided to international colleagues for knowledge sharing and possible collaboration.
Loerch, Linda↗
2023 Artemis Crew Health and Performance System Model Development
While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper
Systems engineering↗
Human-Automation Allocations for Current Robotic Space Operations
Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.
robotic allocation↗