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At least 91 records · Page 5

Step 1: Human System Interface (HSI) Functional Requirements Document (FRD). Version 2

This Functional Requirements Document (FRD) establishes a minimum set of Human System Interface (HSI) functional requirements to achieve the Access 5 Vision of "operating High Altitude, Long Endurance (HALE) Unmanned Aircraft Systems (UAS) routinely, safely, and reliably in the National Airspace System (NAS)". Basically, it provides what functions are necessary to fly UAS in the NAS. The framework used to identify the appropriate functions was the "Aviate, Navigate, Communicate, and Avoid Hazards" structure identified in the Access 5 FRD. As a result, fifteen high-level functional requirements were developed. In addition, several of them have been decomposed into low-level functional requirements to provide more detail.

Source record↗

NASA Space Flight Human System Standards

NASA has begun a new approach to human factors design standards. For years NASA-STD-3000, Manned Systems Integration Standards, has been a source of human factors design guidance for space systems. In order to better meet the needs of the system developers, NASA is revising its human factors standards system. NASA-STD-3000 will be replaced by two documents: set of broad human systems specifications (including both human factors and medical topics) and a human factors design handbook

Tillman, Barry↗

Human System Integration: Regulatory Analysis

This document was intended as an input to the Access 5 Policy Integrated Product team. Using a Human System Integration (HIS) perspective, a regulatory analyses of the FARS (specifically Part 91), the Airman s Information Manual (AIM) and the FAA Controllers Handbook (7110.65) was conducted as part of a front-end approach needed to derive HSI requirements for Unmanned Aircraft Systems (UAS) operations in the National Airspace System above FL430. The review of the above aviation reference materials yielded eighty-four functions determined to be necessary or highly desirable for flight within the Air Traffic Management System. They include categories for Flight, Communications, Navigation, Surveillance, and Hazard Avoidance.

Source record↗

NASA's UAS Integration into the NAS: A Report on the Human Systems Integration Phase 1 Activities

This presentation summarizes the technical activities undertaken by the UAS in the NAS project's Human-Systems Integration team during during it's first phase. The technical activites are discussed in terms of the project's stated mission, research themes and technical challenges. The talk also covers the simulation research that has been performed by the HSI in Phase 1. The end of the presentation lays out the group's plans for Phase 2.

Fern, Lisa↗

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

Computational Models of Trustworthiness and Trust in Autonomous Cyber-Physical-Human Systems

In this paper, we propose an approach to developing a concept of actionable trust in multi-agent,cyber-physical-human systems in safety-critical and time-critical environment of air transportation. Actionable trust requires computational models of trustworthiness and trust, for use during system design and in real time, during operations. We describe the models, examine their computability and scalability, as well as what remains to be done.

Autonomous Systems↗

Human-system Interaction Issues and Proposed Solutions To Promote Successful Maturation of the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

Human-system interaction issues and proposed solutions to promote successful maturation of the UTM system

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

Studying Human-System Interaction within the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity. .

UTM↗

Studying Human-System Interaction with the UTM System

Over five years, NASA, together with partnering organizations, has been developing and successfully demonstrating the maturing capabilities of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) system and its ability to support communication and coordination among small UAS operations through a series of flight tests. During these flight tests, human-system interaction (HSI) elements were also explored in order to identify the barriers to implementation as human operators transitionally fulfill roles that will be ultimately tasked to future automation. Throughout the tests, similar issues were regularly documented and are expected to persist if not formally addressed by consistent procedures or regulation. Documented here, along with suggested mitigations, are the most frequently noted HSI items, which include operator training, data standardization, and information quantity.

UTM↗

Human Systems Integration: Managing Risk in Anesthesia

The practice of anesthesia relies on clinicians’ ability to safely manage increasingly complex equipment. Devices such as ventilators, drug infusion pumps, and physiologic monitors use sophisticated algorithms to deliver care, but most clinicians are only trained to manage automated systems during normal operation. Few if any receive training on how to manage system failures. Although manufacturers are required to consult with human factors engineers as part of the equipment design process, most pieces of equipment are ultimately brought to market without extensive input from clinicians. Systems in the operating room can be as simple as an oxygen tank, or as complex as a multi-institutional healthcare organization. Humans are also a complex system, and play a critical role in the domains of operations, design, fabrication, maintenance, repair, and ultimately, dismantling and closeout. HSI seeks to provide a means for advocating the human side of the system. Human Systems Integration (HSI) is the cross disciplinary process used as part of the Systems Engineering process to reduce risk in systems. HSI professionals consider the human, hardware, and software elements of system design to optimize system performance and improve safety. HSI professionals work in domains of study that include training, management, human factors engineering, safety, and occupational health, among others. This article discusses the role of systems in the practice of anesthesia, and how consideration of the human during all phases of the system life cycle helps manage risks and promote a better patient outcome.

Human Factors↗

Human Systems Integration Relationships Between Deep Space and Deepwater Exploration Challenges

This presentation provides a summary discussion of the paper related to HSI used at NASA and the critical role human factors engineering will play in the HSI process for future missions along with the challenges. Industries such as oil and gas (O&G) could benefit from the content of this paper to help improve the safety and operations of deep water/oil and gas exploration activities. NASA engineering and human systems subject-matter expert personnel reviewed challenges reported in space-related environments for long space duration missions and identified similarities with the challenges encountered in deep water exploration. The researchers noted the space industry's current solutions and proposed a system development view to solve future deep water exploration challenges using HSI principles.

George Salazar↗

Step 1: Human System Integration Pilot-Technology Interface Requirements for Weather Management

This document involves definition of technology interface requirements for Hazardous Weather Avoidance. Technology concepts in use by the Access 5 Weather Management Work Package were considered. Beginning with the Human System Integration (HIS) high-level functional requirement for Hazardous Weather Avoidance, and Hazardous Weather Avoidance technology elements, HSI requirements for the interface to the pilot were identified. Results of the analysis describe (1) the information required by the pilot to have knowledge of hazardous weather, and (2) the control capability needed by the pilot to obtain hazardous weather information. Fundamentally, these requirements provide the candidate Hazardous Weather Avoidance technology concepts with the necessary human-related elements to make them compatible with human capabilities and limitations. The results of the analysis describe how Hazardous Weather Avoidance operations and functions should interface with the pilot to provide the necessary Weather Management functionality to the UA-pilot system. Requirements and guidelines for Hazardous Weather Avoidance are partitioned into four categories: (1) Planning En Route (2) Encountering Hazardous Weather En Route, (3) Planning to Destination, and (4) Diversion Planning Alternate Airport. Each requirement is stated and is supported with a rationale and associated reference(s).

Source record↗

Integrating Spaceflight Human System Risk Research

NASA is working to increase the likelihoods of human health and performance success during exploration missions, and subsequent crew long-term health. To manage the risks in achieving these goals, a system modeled after a Continuous Risk Management framework is in place. "Human System Risks" (Risks) have been identified, and approximately 30 are being actively addressed by NASA's Human Research Program (HRP). Research plans for each of HRP's Risks have been developed and are being executed. Ties between the research efforts supporting each Risk have been identified, however, this has been in an ad hoc fashion. There is growing recognition that solutions developed to address the full set of Risks covering medical, physiological, behavioral, vehicle, and organizational aspects of the exploration missions must be integrated across Risks and disciplines. We will discuss how a framework of factors influencing human health and performance in space is being applied as the backbone for bringing together sometimes disparate information relevant to the individual Risks. The resulting interrelated information is allowing us to identify and visualize connections between Risks and research efforts in a systematic and standardized way. We will discuss the applications of the visualizations and insights to research planning, solicitation, and decision-making processes.

Mindock, J.↗

Developing a Prototype ALHAT Human System Interface for Landing

The goal of the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is to safely execute a precision landing anytime/anywhere on the moon. This means the system must operate in any lighting conditions, operate in the presence of any thruster generated regolith clouds, and operate without the help of redeployed navigational aids or prepared landing site at the landing site. In order to reach this ambitious goal, computer aided technologies such as ALHAT will be needed in order to permit these landings to be done safely. Although there will be advanced autonomous capabilities onboard future landers, humans will still be involved (either onboard as astronauts or remotely from mission control) in any mission to the moon or other planetary body. Because many time critical decisions must be made quickly and effectively during the landing sequence, the Descent and Landing displays need to be designed to be as effective as possible at presenting the pertinent information to the operator, and allow the operators decisions to be implemented as quickly as possible. The ALHAT project has established the Human System Interface (HSI) team to lead in the development of these displays and to study the best way to provide operators enhanced situational awareness during landing activities. These displays are prototypes that were developed based on multiple design and feedback sessions with the astronaut office at NASA/ Johnson Space Center. By working with the astronauts in a series of plan/build/evaluate cycles, the HSI team has obtained astronaut feedback from the very beginning of the design process. In addition to developing prototype displays, the HSI team has also worked to provide realistic lunar terrain (and shading) to simulate a "out the window" view that can be adjusted to various lighting conditions (based on a desired date/time) to allow the same terrain to be viewed under varying lighting terrain. This capability will be critical to determining the effect of terrain/lighting on the human pilot, and how they use windows and displays during landing activities. The Apollo missions were limited to about 28 possible launch days a year due to lighting and orbital constraints. In order to take advantage of more landing opportunities and venture to more challenging landing locations, future landers will need to utilize sensors besides human eyes for scanning the surface. The ALHAT HSI system must effectively convey ALHAT produced information to the operator, so that landings can occur during less "optimal" conditions (lighting, surface terrain, slopes, etc) than was possible during Apollo missions. By proving this capability, ALHAT will simultaneously provide more flexible access to the moon, and greater safety margins for future landers. This paper will specifically focus on the development of prototype displays (the Trajectory Profile Display (TPD), Landing Point Designation (LPD), and Crew Camera View (CCV) ), implementation of realistic planetary terrain, human modeling, and future HSI plans.

Hirsh, Robert L.↗

Integrating Spaceflight Human System Risk Research

NASA is working to increase the likelihood of human health and performance success during exploration missions as well as to maintain the subsequent long-term health of the crew. To manage the risks in achieving these goals, a system modelled after a Continuous Risk Management framework is in place. "Human System Risks" (Risks) have been identified, and approximately 30 are being actively addressed by NASA's Human Research Program (HRP). Research plans for each of HRP's Risks have been developed and are being executed. Inter-disciplinary ties between the research efforts supporting each Risk have been identified; however, efforts to identify and benefit from these connections have been mostly ad hoc. There is growing recognition that solutions developed to address the full set of Risks covering medical, physiological, behavioural, vehicle, and organizational aspects of exploration missions must be integrated across Risks and disciplines. This paper discusses how a framework of factors influencing human health and performance in space is being applied as the backbone for bringing together sometimes disparate information relevant to the individual Risks. The resulting interrelated information enables identification and visualization of connections between Risks and research efforts in a systematic and standardized manner. This paper also discusses the applications of the visualizations and insights into research planning, solicitation, and decision-making processes.

Mindock, Jennifer↗

Applying NASA’s Human Systems Integration Methodology in Implementing Voice-Control of Future Spacecraft Systems

Through the NASA Artemis program, a new era of space exploration will serve to lead humanity towards sustained lunar exploration in preparation for the next giant leap-human exploration of Mars. These crewed spacecraft and habitats will require more automation and autonomy to support these complex missions. Crew size will be small and therefore a more efficient command and control input method is desired. Speech recognition along with visual or auditory feedback is an alternative, providing an extra pair of hands and eyes for the crew. Yet, speech recognition demands a highly integrated development approach to ensure a successful system implementation. To ensure the voice control application is developed correctly will require a Human Systems Integration (HSI) approach. This paper provides an insight into the development of a speech/voice control application for a spacecraft system that encompasses automation and autonomy through an HSI approach. Results of the voice control experiment of the Space Shuttle camera system are provided as lessons learned about using voice control on a spacecraft. Limitations and challenges of the technology are addressed as well as how HSI along with Human Readiness Level can help successfully develop voice control command and control systems.

Systems Engineering↗