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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

2nd Workshop of Human-Automation Interaction Considerations for UAS Integration

NASA's Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project (UAS-NAS) and the UAS Executive Committee (EXCOM) Science and Research Panel (SARP) invite you to attend the 2nd Workshop on Human-Automation Interaction Considerations for UAS Integration. A follow on to the workshop hosted by the National Academies of Science, Engineering and Medicine, this two-day workshop aims to tackle two critical issues for UAS integration in the NAS being addressed by NASA and the SARP: control of multiple UAS by a single, or multiple, operators (multi-UAS), and automatic collision avoidance (auto-CA). Attendees will be asked to generate real human-automation architecture and human machine interface solutions for these problems during interactive breakout sessions. Attendance is limited to select government and academia invitees only. This presentation is outlines the objectives of the workshop.

human-automation interaction↗
NASA NTRS2010

A Toolset for Supporting Iterative Human Automation: Interaction in Design

The addition of automation has greatly extended humans' capability to accomplish tasks, including those that are difficult, complex and safety critical. The majority of Human - Automation Interact~on (HAl) results in more efficient and safe operations, ho,,:,ever ~ertain un~~pected a~tomatlon behaviors or "automation surprises" can be frustrating and, In certain safety critical operations (e.g. transport~tion, manufacturing control, medicine), may result in injuries or. the loss of life.. (Mellor, 1994; Leveson, 1995; FAA, 1995; BASI, 1998; Sheridan, 2002). This pap~r describes ~he development of a design tool that enables on the rapid development and evaluation. of automat~on prototypes. The ultimate goal of the work is to provide a design platform upon which automation surprise vulnerability analyses can be integrated.

Feary, Michael S.↗
NASA NTRS1993

Modeling strategic behavior in human-automation interaction - Why an 'aid' can (and should) go unused

Task-offload aids (e.g., an autopilot, an 'intelligent' assistant) can be selectively engaged by the human operator to dynamically delegate tasks to automation. Introducing such aids eliminates some task demands but creates new ones associated with programming, engaging, and disengaging the aiding device via an interface. The burdens associated with managing automation can sometimes outweigh the potential benefits of automation to improved system performance. Aid design parameters and features of the overall multitask context combine to determine whether or not a task-offload aid will effectively support the operator. A modeling and sensitivity analysis approach is presented that identifies effective strategies for human-automation interaction as a function of three task-context parameters and three aid design parameters. The analysis and modeling approaches provide resources for predicting how a well-adapted operator will use a given task-offload aid, and for specifying aid design features that ensure that automation will provide effective operator support in a multitask environment.

Kirlik, Alex↗
NASA NTRS1991

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Kirlik, Alex↗
NASA NTRSDate not supplied

Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and Workload

Technological advances have increased the automation of Uncrewed Aerial Vehicles, allowing human operators to manage multiple vehicles at a high-level without the need to understand low-level system behaviors. Previous laboratory studies have explored the relationship between reliability, trust, use of automation and the effects of number of vehicles under supervision on subjective workload. Due to the limitations resulting from the COVID-19 pandemic, in-person laboratory studies are not always possible. Therefore, this work aimed to investigate if remote data collection alternatives, such as Amazon’s Mechanical Turk, can provide comparative results as those obtained in laboratory settings. A study was conducted in the context of small drone operations. As expected, higher reliability led to higher trust ratings and the inclusion of more vehicles led to higher workload. In contrast, reliability unexpectedly had no effect on intention to use the automation. Though these results were encouraging, several limitations were identified.

trust↗
NASA NTRS2002

Formal verification of human-automation interaction

This paper discusses a formal and rigorous approach to the analysis of operator interaction with machines. It addresses the acute problem of detecting design errors in human-machine interaction and focuses on verifying the correctness of the interaction in complex and automated control systems. The paper describes a systematic methodology for evaluating whether the interface provides the necessary information about the machine to enable the operator to perform a specified task successfully and unambiguously. It also addresses the adequacy of information provided to the user via training material (e.g., user manual) about the machine's behavior. The essentials of the methodology, which can be automated and applied to the verification of large systems, are illustrated by several examples and through a case study of pilot interaction with an autopilot aboard a modern commercial aircraft. The expected application of this methodology is an augmentation and enhancement, by formal verification, of human-automation interfaces.

Aviation↗
NASA NTRSDate not supplied

Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and Workload

Introduction - Paradigm shift from one operator supervising a single vehicle, to an operator supervising multiple highly automated vehicles (One-to-Many) - One-to-Many application - Search and Rescue - Foraging - Military ops - Etc. - Calibrated trust in automation enables human operators to effectively manage highly automated vehicles - Past studies show that trust mediates relationship between reliability and dependence (Chancey et al., 2017; Chancey et al., 2015) - Future studies needed to further understand relationship

trust↗
NASA NTRS2014

Some Challenges in the Design of Human-Automation Interaction for Safety-Critical Systems

Increasing amounts of automation are being introduced to safety-critical domains. While the introduction of automation has led to an overall increase in reliability and improved safety, it has also introduced a class of failure modes, and new challenges in risk assessment for the new systems, particularly in the assessment of rare events resulting from complex inter-related factors. Designing successful human-automation systems is challenging, and the challenges go beyond good interface development (e.g., Roth, Malin, & Schreckenghost 1997; Christoffersen & Woods, 2002). Human-automation design is particularly challenging when the underlying automation technology generates behavior that is difficult for the user to anticipate or understand. These challenges have been recognized in several safety-critical domains, and have resulted in increased efforts to develop training, procedures, regulations and guidance material (CAST, 2008, IAEA, 2001, FAA, 2013, ICAO, 2012). This paper points to the continuing need for new methods to describe and characterize the operational environment within which new automation concepts are being presented. We will describe challenges to the successful development and evaluation of human-automation systems in safety-critical domains, and describe some approaches that could be used to address these challenges. We will draw from experience with the aviation, spaceflight and nuclear power domains.

systems engineering↗
NASA NTRS1998

Formal Analysis of Human Automation Interaction: The Problem of Display Correctness

This presentation attempted to develop a quantitative method for evaluating the effectiveness of autoflight displays. Researchers sought to develop a methodology for evaluation of display correctness and develop a methodology for display synthesis. Topics covered included: mode awareness, industry/research contributions, human-machine interface analysis, research objectives, modeling, flight guidance project and evaluation.

Degani, Asaf↗
NASA NTRS1998

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↗
DOE OSTI2021

Human-automated vehicle interactions

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗
DOE OSTI2021

HUMAN-AUTOMATED VEHICLE INTERACTIONS

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗
NASA NTRS2015

Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system failures and anomalies of avionic systems are also incorporated. The resultant model helps simulate the emergence of automation-related issues in today's modern airliners from a top-down, generalized approach, which serves as a platform to evaluate NASA developed technologies

Ancel, Ersin↗
NASA NTRS2011

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↗
NASA NTRS2020

Designing and Training for Appropriate Trust in Increasingly Autonomous Advanced Air Mobility Operations: A Mental Model Approach: Version 1

To enable effective human-autonomy teaming (HAT) in Advanced Air Mobility (AAM) operations, the current paper presents a theoretical framework to design and train for appropriate trust in automation. The novel contribution of this work resides in connecting the construct of trust to mental models and showing how this method could be used to enable emerging HAT concepts such as Adaptive Trust Calibration. To contextualize this framework, in section 2 we discuss simplified vehicle operations (SVO) and remote vehicle operations (RVO), which are leading operational concepts within AAM. In section 3 we describe our perspective on automation and increasingly autonomous systems and present a brief discussion on human-automation interaction and human-autonomy teaming. In section 4 we provide a detailed discussion on the construct of trust in automation. In section 5 we present a framework that associates mental models with trust through principles of transparent design. Finally, in section 6 we present three descriptive models for designing and training for appropriate trust in increasingly autonomous systems.

Human-Autonomy Teaming↗
NASA NTRS2003

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↗
NASA NTRS2015

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.↗
NASA NTRS2003

Three Experiments Examining the Use of Electroencephalogram,Event-Related Potentials, and Heart-Rate Variability for Real-Time Human-Centered Adaptive Automation Design

Adaptive automation represents an advanced form of human-centered automation design. The approach to automation provides for real-time and model-based assessments of human-automation interaction, determines whether the human has entered into a hazardous state of awareness and then modulates the task environment to keep the operator in-the-loop , while maintaining an optimal state of task engagement and mental alertness. Because adaptive automation has not matured, numerous challenges remain, including what the criteria are, for determining when adaptive aiding and adaptive function allocation should take place. Human factors experts in the area have suggested a number of measures including the use of psychophysiology. This NASA Technical Paper reports on three experiments that examined the psychophysiological measures of event-related potentials, electroencephalogram, and heart-rate variability for real-time adaptive automation. The results of the experiments confirm the efficacy of these measures for use in both a developmental and operational role for adaptive automation design. The implications of these results and future directions for psychophysiology and human-centered automation design are discussed.

Prinzel, Lawrence J., III↗