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At least 55 records · Page 3

Achieving Resilient In-Flight Performance for Advanced Air Mobility through Simplified Vehicle Operations

A research and development (R&D) approach is proposed for developing and validating concepts and technologies to achieve vehicle autonomy goals of Advanced Air Mobility (AAM) through Simplified Vehicle Operations (SVO). The approach applies resilience-engineering and human-automation teaming (HAT) principles to a framework for defining vehicle-based functions for the management of missions and flight trajectories, focusing initially on the en route flight domain. To achieve the SVO goal of reducing pilot training requirements and thereby increasing the pilot pool for AAM, while at the same time promoting ever-safer operations, a framework for identifying essential functions is proposed. In this framework, functions are first categorized by high-level functional purpose (mission management, flightpath management, tactical operations, and vehicle control) and then subcategorized by attributes of resilient-performing systems (abilities to monitor, respond, learn, and anticipate). The categorization by functional purpose provides structure within which HAT designs can be holistically explored and total levels of human vs. automation responsibility can be varied. The subcategorization by resilient-system attributes provides a mechanism for capturing safety-critical functions that may not be codified in current operational procedures and training curricula, particularly those where humans proactively enhance safety in currently undocumented ways. An R&D approach consisting of seven strategies is proposed in which automation engineering and human-factors communities can collaborate in the research, development, and design of an SVO roadmap to enable the ambitious objectives of AAM.

AAM↗

M:N Operations NASA/Uber Collaboration

In this presentation, current approaches to enable multiple-operator, multiple vehicle (M:N) operations are reviewed together with recent collaborative efforts between NASA and Uber. Topics include a review of human-automation teaming (HAT) concepts, including plays and working agreements, and a particular task-allocation method called Automation Level-based Task Allocation (ALTA). Following introductory material on HAT, an overview of a recent (July 2020) cognitive walkthrough study of M:N operations in the context of a food delivery via small-Unmanned Aircraft Systems application is provided. Initial results from this cognitive walkthrough detailing operator feedback on displays, operator and supervisor roles and responsibilities, and the overall concept of operation are reviewed. The presentation concludes with a description of a future, human-in-the-loop simulation experiment of M:N operations in a high-fidelity environment, which will examine the effects of high workload and assistive automation/tools on operator performance.

human-automation teaming↗

On Abstractions and Simplifications in the Design of Human-Automation Interfaces

This report addresses the design of human-automation interaction from a formal perspective that focuses on the information content of the interface, rather than the design of the graphical user interface. It also addresses the, issue of the information provided to the user (e.g., user-manuals, training material, and all other resources). In this report, we propose a formal procedure for generating interfaces and user-manuals. The procedure is guided by two criteria: First, the interface must be correct, i.e., that with the given interface the user will be able to perform the specified tasks correctly. Second, the interface should be as succinct as possible. The report discusses the underlying concepts and the formal methods for this approach. Several examples are used to illustrate the procedure. The algorithm for constructing interfaces can be automated, and a preliminary software system for its implementation has been developed.

Heymann, Michael↗

Formal Aspects of Human-Automation Interaction

While new versions of automated control systems such as flight guidance systems are introduced at a rapid pace, it is widely recognized that user interaction with these machines is increasingly problematic. One cause for this difficulty that is commonly cited in the literature, is the discrepancy between the machine's behavior and the operator's (e.g., pilot) expectations. This paper discusses a formal approach to the analysis of operator's interaction with complex automated control systems. We focus attention on the issue of interface correctness; that is, on the question whether the display provides adequate information about the machine's configurations (states, modes, and associated parameters) and transitions, so as to enable the operator to successfully perform the specified set of tasks. To perform the analysis several assumptions are made: (1) A complete formal model of the machine's behavior is available (e.g., as a state transition system, or as a hybrid-machine); (2) A specification of operator's tasks is available and can be formally described (e.g., the reliable and predictable transition between activities involved in executing a climb to a new altitude); (3) The pilot is well trained and has a correct 'mental' model of the machine's response-map. By 'comparing' the machine's model with the set of operator's tasks we formally (i.e., mathematically) evaluate two questions: 1) does the machine's output interface (display) enable the operator to determine, unambiguously, what the current configuration (e.g., mode) of the machine is, and 2) does the display enable the operator to determine, unambiguously, what the next configuration of the machine will be, in response to a specified interaction by the operator (e.g., engaging a mode or changing a parameter such as a speed or target altitude). This paper describes a methodology for conducting such an evaluation using examples from automated flight control systems of modem 'glass cockpit' jetliners. Taxonomy of the different types of discrepancies that lead to pilot inability to resolve the current and next configuration of the machine is suggested. Data from incident reports involving 'mode confusion' is used to corroborate these discrepancies. Finally, means for compensating, either by augmenting the display and/or the operator's 'mental model' are briefly mentioned.

Degani, Asaf↗

On Abstractions and Simplifications in the Design of Human-Automation Interfaces

This report addresses the design of human-automation interaction from a formal perspective that focuses on the information content of the interface, rather than the design of the graphical user interface. It also addresses the issue of the information provided to the user (e.g., user-manuals, training material, and all other resources). In this report, we propose a formal procedure for generating interfaces and user-manuals. The procedure is guided by two criteria: First, the interface must be correct, that is, with the given interface the user will be able to perform the specified tasks correctly. Second, the interface should be succinct. The report discusses the underlying concepts and the formal methods for this approach. Two examples are used to illustrate the procedure. The algorithm for constructing interfaces can be automated, and a preliminary software system for its implementation has been developed.

Heymann, Michael↗

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

Kaber, David B.↗

Team-Centered Perspective for Adaptive Automation Design

Automation represents a very active area of human factors research. The journal, Human Factors, published a special issue on automation in 1985. Since then, hundreds of scientific studies have been published examining the nature of automation and its interaction with human performance. However, despite a dramatic increase in research investigating human factors issues in aviation automation, there remain areas that need further exploration. This NASA Technical Memorandum describes a new area of automation design and research, called adaptive automation. It discusses the concepts and outlines the human factors issues associated with the new method of adaptive function allocation. The primary focus is on human-centered design, and specifically on ensuring that adaptive automation is from a team-centered perspective. The document shows that adaptive automation has many human factors issues common to traditional automation design. Much like the introduction of other new technologies and paradigm shifts, adaptive automation presents an opportunity to remediate current problems but poses new ones for human-automation interaction in aerospace operations. The review here is intended to communicate the philosophical perspective and direction of adaptive automation research conducted under the Aerospace Operations Systems (AOS), Physiological and Psychological Stressors and Factors (PPSF) project.

Prinzel, Lawrence J., III↗

Team play with a powerful and independent agent: operational experiences and automation surprises on the Airbus A-320

Research and operational experience have shown that one of the major problems with pilot-automation interaction is a lack of mode awareness (i.e., the current and future status and behavior of the automation). As a result, pilots sometimes experience so-called automation surprises when the automation takes an unexpected action or fails to behave as anticipated. A lack of mode awareness and automation surprises can he viewed as symptoms of a mismatch between human and machine properties and capabilities. Changes in automation design can therefore he expected to affect the likelihood and nature of problems encountered by pilots. Previous studies have focused exclusively on early generation "glass cockpit" aircraft that were designed based on a similar automation philosophy. To find out whether similar difficulties with maintaining mode awareness are encountered on more advanced aircraft, a corpus of automation surprises was gathered from pilots of the Airbus A-320, an aircraft characterized by high levels of autonomy, authority, and complexity. To understand the underlying reasons for reported breakdowns in human-automation coordination, we also asked pilots about their monitoring strategies and their experiences with and attitude toward the unique design of flight controls on this aircraft.

NASA Discipline Space Human Factors↗

Automated Test Case Generation for an Autopilot Requirement Prototype

Designing safety-critical automation with robust human interaction is a difficult task that is susceptible to a number of known Human-Automation Interaction (HAI) vulnerabilities. It is therefore essential to develop automated tools that provide support both in the design and rapid evaluation of such automation. The Automation Design and Evaluation Prototyping Toolset (ADEPT) enables the rapid development of an executable specification for automation behavior and user interaction. ADEPT supports a number of analysis capabilities, thus enabling the detection of HAI vulnerabilities early in the design process, when modifications are less costly. In this paper, we advocate the introduction of a new capability to model-based prototyping tools such as ADEPT. The new capability is based on symbolic execution that allows us to automatically generate quality test suites based on the system design. Symbolic execution is used to generate both user input and test oracles user input drives the testing of the system implementation, and test oracles ensure that the system behaves as designed. We present early results in the context of a component in the Autopilot system modeled in ADEPT, and discuss the challenges of test case generation in the HAI domain.

Giannakopoulou, Dimitra↗

An Extended Case Study Methoology for Investigating Influence of Cultural, Organizational, and Automation Factors on Human-Automation Trust

This paper discusses a case study that examined the influence of cultural, organizational and automation capability upon human trust in, and reliance on, automation. In particular, this paper focuses on the design and application of an extended case study methodology, and on the foundational lessons revealed by it. Experimental test pilots involved in the research and development of the US Air Forces newly developed Automatic Ground Collision Avoidance System served as the context for this examination. An eclectic, multi-pronged approach was designed to conduct this case study, and proved effective in addressing the challenges associated with the cases politically sensitive and military environment. Key results indicate that the system design was in alignment with pilot culture and organizational mission, indicating the potential for appropriate trust development in operational pilots. These include the low-vulnerabilityhigh risk nature of the pilot profession, automation transparency and suspicion, system reputation, and the setup of and communications among organizations involved in the system development.

automation suspicion↗

Human Factors and Habitability Challenges for Mars Missions

As NASA is planning to send humans deeper into space than ever before, adequate crew health and performance will be critical for mission success. Within the NASA Human Research Program (HRP), the Space Human Factors and Habitability (SHFH) team is responsible for characterizing the risks associated with human capabilities and limitations with respect to long-duration spaceflight, and for providing mitigations (e.g., guidelines, technologies, and tools) to promote safe, reliable and productive missions. SHFH research includes three domains: Advanced Environmental Health (AEH), Advanced Food Technology (AFT), and Space Human Factors Engineering (SHFE). The AEH portfolio focuses on understanding the risk of microbial contamination of the spacecraft and on the development of standards for exposure to potential toxins such as chemicals, bacteria, fungus, and lunar/Martian dust. The two risks that the environmental health project focuses on are adverse health effects due to changes in host-microbe interactions, and risks associated with exposure to dust in planetary surface habitats. This portfolio also proposes countermeasures to these risks by making recommendations that relate to requirements for environmental quality, foods, and crew health on spacecraft and space missions. The AFT portfolio focuses on reducing the mass, volume, and waste of the entire integrated food system to be used in exploration missions, and investigating processing methods to extend the shelf life of food items up to five years, while assuring that exploration crews will have nutritious and palatable foods. The portfolio also delivers improvements in both the food itself and the technologies for storing and preparing it. SHFE sponsors research to establish human factors and habitability standards and guidelines in five risk areas, and provides improved design concepts for advanced crew interfaces and habitability systems. These risk areas include: Incompatible vehicle/habitat design, inadequate human-computer interaction, inadequate critical task design, inadequate human-automation/robotic interaction, and performance errors due to training deficiencies. To address the identified research gaps within each risk, SHFH's research plan includes studies in the laboratory, in analogs, and on International Space Station (ISS). In addition to establishing and maintaining the risk-based research portfolio, SHFH is also implementing a qualitative approach to determine how we at NASA evaluate human performance. Via interviews with experts, such as trainers, flight controllers, and flight surgeons, we are collecting the metrics by which they assess human performance, evidence of performance issues, and potential or actual consequences. The Human Performance Data Project will determine what human performance data have been collected in the past at NASA, and what data should be collected in the future in order to complete our knowledgebase and reduce risks related to human factors and habitability.

Whitmore, Mihriban↗

Analysis of Aviation Safety Reporting System Incident Data Associated with the Technical Challenges of the System-Wide Safety and Assurance Technologies Project

The Aviation Safety Program (AvSP) System-Wide Safety and Assurance Technologies (SSAT) Project asked the AvSP Systems and Portfolio Analysis Team to identify SSAT-related trends. SSAT had four technical challenges: advance safety assurance to enable deployment of NextGen systems; automated discovery of precursors to aviation safety incidents; increasing safety of human-automation interaction by incorporating human performance, and prognostic algorithm design for safety assurance. This report reviews incident data from the NASA Aviation Safety Reporting System (ASRS) for system-component-failure- or-malfunction- (SCFM-) related and human-factor-related incidents for commercial or cargo air carriers (Part 121), commuter airlines (Part 135), and general aviation (Part 91). The data was analyzed by Federal Aviation Regulations (FAR) part, phase of flight, SCFM category, human factor category, and a variety of anomalies and results. There were 38 894 SCFM-related incidents and 83 478 human-factorrelated incidents analyzed between January 1993 and April 2011.

Withrow, Colleen A.↗

Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault-tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

safety-critical automation↗

Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under different function-allocation approaches aligned with four increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting the controller to exceptional circumstances. Results indicate that overall performance was best in the most automated NextGen environment. Safe operations were achieved in this environment for twice todays peak airspace capacity, while being rated by the controllers as highly acceptable. However, results show that sector operations were not always safe; separation violations did in fact occur. This paper will describe in detail the simulation conducted, as well discuss important results and their implications.

air traffic control↗

A First Look at the Evolution of Flight Crew Requirements for Emerging Market Aircraft

This is an exciting time for aviation. New vehicle and airspace technologies promise large increases in the number of aircraft in operation. One critical technology for these emerging markets is the increased use of automated systems to reduce pilot skill, training, and proficiency requirements. While the use of these systems promises to reduce or eliminate pilot functions in the long-term, the technology development for the required functions will necessitate a phased transition. The transition to, and adoption of automated systems will generate new safety challenges. This paper is a first look at a model to help frame flight crew functions for evaluation of future operational requirements. The model is intended to provide required flight crew functions regardless of whether the functions are performed by human or artificial agent. It is hoped that the model will be useful in identifying safety challenges and enabling a safe transition for the new aviation markets. The paper presents some background for a model for framing the flight crew function model and some thoughts about next steps.

safety-critical automation↗

A Closer Look at Automation Behavior During a Human-in-the-Loop Simulation

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under four different function allocation concepts aligned with increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting controllers to exceptional circumstances. This paper continues the investigations reported in previous publications. Analyses of data surrounding the conflict-resolution task serve as the context in which we investigate the interactions between controllers and the automation.

Human-Automation Interaction↗

Thinking outside the box: The human role in increasingly automated aviation systems

Rapid advances in artificial intelligence are enabling automated systems to operate in an increasingly autonomous manner in domains that previously required the involvement of human operators. Examples are rail transport systems, self-driving cars, and warehouse delivery systems. From time to time, such automation encounters operational conditions that fall outside a “competency box” within which the system has been designed to operate. Human operators add resilience because they can see and act outside the competency box of scenarios and environments for which the system was designed. The system’s competencies can be expanded over time with modifications to software, sensors, etc.; however, it is unclear at what point the competency box becomes large enough to safely eliminate the role of the human operator. One area where advanced automation may be applied is Urban Air Mobility (UAM). Current UAM concepts envision fleets of highly automated air vehicles providing on-demand transport for people and goods. A phased development of UAM has been proposed, beginning with on-board pilots and transitioning to a future state where automated vehicles operate with minimal human involvement. Proponents of UAM note that this final state reduces cost as well as eliminating pilot error, identified as a contributing factor in many aircraft accidents. However, eliminating human involvement also risks eliminating their positive contributions to system resilience. Here we examine Concepts of Operation proposed for future UAM systems and explore how humans can best be incorporated to maintain resilience while minimizing cost and risk. A human-autonomy teaming approach is suggested.

Advanced Air Mobility↗

Automation & Autonomy Standards and Guidelines for Space Vehicles

The NASA Office of the Chief Health and Medical Officer (OCHMO) requested HRP conduct a survey of industry and government standards and guidelines for the interaction of automation/autonomy with humans. Guidance for verification testing of human-automation designs was also requested. A rapid response was requested so that the deliverables could be provided as part of a future NASA solicitation for automated systems for HLS. The project began with a broad review and analysis of prior NASA work in this area, as well as external standards related to human interaction with automation/autonomy. The team reviewed approximately 200 documents, and interviewed multiple industry and government subject matter experts (SMEs). “Gold standard” documents were selected for focus and key categories were identified. A cross-walk of standards was created, and common standards and guidelines were selected and rephrased (where necessary) to be information-rich, concise, and usable. Verification guidelines and examples were also developed. The final report includes an introduction to automation and autonomy, selected standards and guidelines, verification method guidance, and research gaps. In addition to the report, the team delivered a list of candidate standards for autonomous vehicles, as well as a list of candidate standards for a future NASA-STD-3001 update on automation/autonomy. The presentation will describe the rapid response project approach and methods, examples of standards and guidelines identified and delivered to OCHMO, and research needed to develop additional automation/autonomy design guidance where gaps currently exist.

automation↗