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NASA NTRS1990

Evolution paths for advanced automation

As Space Station Freedom (SSF) evolves, increased automation and autonomy will be required to meet Space Station Freedom Program (SSFP) objectives. As a precursor to the use of advanced automation within the SSFP, especially if it is to be used on SSF (e.g., to automate the operation of the flight systems), the underlying technologies will need to be elevated to a high level of readiness to ensure safe and effective operations. Ground facilities supporting the development of these flight systems -- from research and development laboratories through formal hardware and software development environments -- will be responsible for achieving these levels of technology readiness. These facilities will need to evolve support the general evolution of the SSFP. This evolution will include support for increasing the use of advanced automation. The SSF Advanced Development Program has funded a study to define evolution paths for advanced automaton within the SSFP's ground-based facilities which will enable, promote, and accelerate the appropriate use of advanced automation on-board SSF. The current capability of the test beds and facilities, such as the Software Support Environment, with regard to advanced automation, has been assessed and their desired evolutionary capabilities have been defined. Plans and guidelines for achieving this necessary capability have been constructed. The approach taken has combined indepth interviews of test beds personnel at all SSF Work Package centers with awareness of relevant state-of-the-art technology and technology insertion methodologies. Key recommendations from the study include advocating a NASA-wide task force for advanced automation, and the creation of software prototype transition environments to facilitate the incorporation of advanced automation in the SSFP.

Healey, Kathleen J.↗

NASA NTRS1997

Automation Bias: Decision Making and Performance in High-Tech Cockpits

Automated aids and decision support tools are rapidly becoming indispensible tools in high-technology cockpits, and are assuming increasing control of "cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate "automation bias," a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation "events," or opportunities for automation-related omission and commission errors. Pilots who perceived themselves as "accountable" for their performance and strategies of interaction with the automation were more likely to double-check automated functioning against other cues, and less likely to commit errors. Pilots were also likely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Mosier, Kathleen L.↗

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↗

NASA NTRS2007

Physiological Self-Regulation and Adaptive Automation

Adaptive automation has been proposed as a solution to current problems of human-automation interaction. Past research has shown the potential of this advanced form of automation to enhance pilot engagement and lower cognitive workload. However, there have been concerns voiced regarding issues, such as automation surprises, associated with the use of adaptive automation. This study examined the use of psychophysiological self-regulation training with adaptive automation that may help pilots deal with these problems through the enhancement of cognitive resource management skills. Eighteen participants were assigned to 3 groups (self-regulation training, false feedback, and control) and performed resource management, monitoring, and tracking tasks from the Multiple Attribute Task Battery. The tracking task was cycled between 3 levels of task difficulty (automatic, adaptive aiding, manual) on the basis of the electroencephalogram-derived engagement index. The other two tasks remained in automatic mode that had a single automation failure. Those participants who had received self-regulation training performed significantly better and reported lower National Aeronautics and Space Administration Task Load Index scores than participants in the false feedback and control groups. The theoretical and practical implications of these results for adaptive automation are discussed.

Prinzell, Lawrence J.↗

NASA NTRS2014

Assessing V and V Processes for Automation with Respect to Vulnerabilities to Loss of Airplane State Awareness

Automation has contributed substantially to the sustained improvement of aviation safety by minimizing the physical workload of the pilot and increasing operational efficiency. Nevertheless, in complex and highly automated aircraft, automation also has unintended consequences. As systems become more complex and the authority and autonomy (A&A) of the automation increases, human operators become relegated to the role of a system supervisor or administrator, a passive role not conducive to maintaining engagement and airplane state awareness (ASA). The consequence is that flight crews can often come to over rely on the automation, become less engaged in the human-machine interaction, and lose awareness of the automation mode under which the aircraft is operating. Likewise, the complexity of the system and automation modes may lead to poor understanding of the interaction between a mode of automation and a particular system configuration or phase of flight. These and other examples of mode confusion often lead to mismanaging the aircraftâ€"TM"s energy state or the aircraft deviating from the intended flight path. This report examines methods for assessing whether, and how, operational constructs properly assign authority and autonomy in a safe and coordinated manner, with particular emphasis on assuring adequate airplane state awareness by the flight crew and air traffic controllers in off-nominal and/or complex situations.

Whitlow, Stephen↗

NASA NTRS2013

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System↗

NASA NTRS2014

Human Factors of Automation in the Airline Cockpit

The introduction of automation to the automobile is following an approach similar to that used to bring automation to the airline cockpit. As technologies incrementally became available to automate portions of the flying task, pilots were left to perform those portions of the task for which engineers were still working towards automating. A number of problems have resulted from this process of gradual takeover of a job once performed entirely by humans. Pilots struggle to maintain awareness of a task with which they are no longer intimately involved and of complex technologies that they do not fully understand. Particularly difficult problems arise when increasingly reliable automated systems reach the limits of their capabilities and require pilots to suddenly exercise manual control and reasoning skills that have slipped away as a result of disuse. We argue that car automation will face these problems and more. Aviation enjoys a broad system of redundancies and safety nets, and, high in the sky, more time to address any problems that arise. We review the literature describing problems that were observed as automation was introduced to the airline cockpit and invite car automation designers to consider how they might play out as technology is gradually introduced to cars and drivers.

Casner, Stephen↗

DOE OSTI2023

Automated Electric Vehicle Fleet Operations for On-Demand Service: Challenges and Opportunities

Automated/autonomous vehicle fleet operations within automated mobility districts have been studied over the past five years by the National Renewable Energy Laboratory, a US Department of Energy federally funded research and development center. This paper extends the analysis in this third phase of research underway to include considerations for electric vehicle operations and charging within a fleet of right-sized automated vehicles providing on-demand public mobility services. The current focus of research is on the operational complexities and associated challenges for automated/autonomous vehicles employing electric drivetrains and the resultant need for an efficient battery charging process while vehicles are operating in an "on-demand" mode of service. The blossoming of microtransit with shared-ride and point-to-point dispatching of each vehicle instills complex operations, with multiple mobility-on-demand transit operating sites being deployed, studied, and analyzed across North America. As a starting point, the authors' experience over the past 20 years with the analysis of automated transit network systems operating on and within dedicated and protected transitways provides initial insights into the system-level operational implications for maintaining a sufficient battery charge for a fleet of automated vehicles. Lessons learned through the prior analyses of automated transit network systems operating in on-demand service are identified, along with the capital cost implications for the requisite operating fleet size and charging station infrastructure for various approaches. These costs are summarized in juxtaposition with the benefits of realizing the higher goals of reducing environmental impacts and energy use within automated mobility districts as automated/autonomous vehicle technology matures. Finally, the discussion addresses key aspects of battery-electric propulsion for managed fleets in fully automated operation that will be studied as the third phase of research continues.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation

Trust calibration for a human–machine team is the process by which a human adjusts their expectations of the automation’s reliability and trustworthiness; adaptive support for trust calibration is needed to engender appropriate reliance on automation. Herein, we leverage an instance-based learning ACT-R cognitive model of decisions to obtain and rely on an automated assistant for visual search in a UAV interface. This cognitive model matches well with the human predictive power statistics measuring reliance decisions; we obtain from the model an internal estimate of automation reliability that mirrors human subjective ratings. The model is able to predict the effect of various potential disruptions, such as environmental changes or particular classes of adversarial intrusions on human trust in automation. Finally, we consider the use of model predictions to improve automation transparency that account for human cognitive biases in order to optimize the bidirectional interaction between human and machine through supporting trust calibration. The implications of our findings for the design of reliable and trustworthy automation are discussed.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Automated Mobility Districts Toolkit

On-demand transportation services have seen a dramatic rise in the past decade, thanks to technology. Connected and automated vehicle (CAV) technology holds potential for a major transformation in the on-demand mobility services landscape.The timeline for fully automated vehicles (AVs) to reach the critical market share is still uncertain. In the short term, many cities in the United States and abroad are testing low-speed automated electric shuttles (AES) as a shared on-demand mobility service in geo-fenced regions. This presentation provides information about the development of the Automated Mobility District (AMD) Toolkit, which features an assortment of modeling and simulation capabilities. An AMD is a campus-sized implementation of connected and automated vehicle technologies that realize all the benefits of a fully electric automated mobility service within a confined region or district.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2017

Application of automated measurement and verification to utility energy efficiency program data

Trustworthy savings calculations are critical to convincing regulators of both the cost-effectiveness of energy efficiency program investments and their ability to defer supply-side capital investments. Today’s methods for measurement and verification (M&V) of energy savings constitute a significant portion of the total costs of energy efficiency programs. They also require time-consuming data acquisition. A spectrum of savings calculation approaches is used, with some relying more heavily on measured data and others relying more heavily on estimated, modeled, or stipulated data. The increasing availability of “smart” meters and devices that report near-real time data, combined with new analytical approaches to quantify savings, offers the potential to conduct M&V more quickly and at lower cost, with comparable or improved accuracy. Commercial energy management and information systems (EMIS) technologies are beginning to offer these ‘M&V 2.0’ capabilities, and program administrators want to understand how they might assist programs in quickly and accurately measuring energy savings. This paper presents the results of recent testing of the ability to use automation to streamline the M&V process. In this paper, we apply an automated whole-building M&V tool to historic data sets from energy efficiency programs to begin to explore the accuracy, cost, and time trade-offs between more traditional M&V, and these emerging streamlined methods that use high-resolution energy data and automated computational intelligence. For the data sets studied we evaluate the fraction of buildings that are well suited to automated baseline characterization, the uncertainty in gross savings that is due to M&V 2.0 tools’ model error, and indications of labor time savings, and how the automated savings results compare to prior, traditionally determined savings results. The results show that 70% of the buildings were well suited to the automated approach. In a majority of the cases (80%) savings and uncertainties for each individual building were quantified to levels above the criteria in ASHRAE Guideline 14. In addition the findings suggest that M&V 2.0 methods may also offer time-savings relative to traditional approaches. Lastly, we discuss the implications of these findings relative to the potential evolution of M&V, and pilots currently being launched to test how M&V automation can be integrated into ratepayer-funded programs and professional implementation and evaluation practice.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Model-centric distribution automation: Capacity, reliability, and efficiency

A series of analyses along with field validations that evaluate efficiency, reliability, and capacity improvements of model-centric distribution automation are presented. With model-centric distribution automation, the same model is used from design to real-time control calculations. A 14-feeder system with 7 substations is considered. The analyses involve hourly time-varying loads and annual load growth factors. Phase balancing and capacitor redesign modifications are used to better prepare the system for distribution automation, where the designs are performed considering time-varying loads. Coordinated control of load tap changing transformers, line regulators, and switched capacitor banks is considered. In evaluating distribution automation versus traditional system design and operation, quasi-steady-state power flow analysis is used. In evaluating distribution automation performance for substation transformer failures, reconfiguration for restoration analysis is performed. In evaluating distribution automation for storm conditions, Monte Carlo simulations coupled with reconfiguration for restoration calculations are used. As a result, the evaluations demonstrate that model-centric distribution automation has positive effects on system efficiency, capacity, and reliability.

25 ENERGY STORAGE↗

DOE OSTI2016

SU-G-BRB-04: Automated Output Factor Measurements Using Continuous Data Logging for Linac Commissioning

Purpose: Linac commissioning is a time consuming and labor intensive process, the streamline of which is highly desirable. In particular, manual measurement of output factors for a variety of field sizes and energy greatly hinders the commissioning efficiency. In this study, automated measurement of output factors was demonstrated as ‘one-click’ using data logging of an electrometer. Methods: Beams to be measured were created in the recording and verifying (R&V) system and configured for continuous delivery. An electrometer with an automatic data logging feature enabled continuous data collection for all fields without human intervention. The electrometer saved data into a spreadsheet every 0.5 seconds. A Matlab program was developed to analyze the excel data to monitor and check the data quality. Results: For each photon energy, output factors were measured for five configurations, including open field and four wedges. Each configuration includes 72 fields sizes, ranging from 4×4 to 20×30 cm{sup 2}. Using automation, it took 50 minutes to complete the measurement of 72 field sizes, in contrast to 80 minutes when using the manual approach. The automation avoided the necessity of redundant Linac status checks between fields as in the manual approach. In fact, the only limiting factor in such automation is Linac overheating. The data collection beams in the R&V system are reusable, and the simplified process is less error-prone. In addition, our Matlab program extracted the output factors faithfully from data logging, and the discrepancy between the automatic and manual measurement is within ±0.3%. For two separate automated measurements 30 days apart, consistency check shows a discrepancy within ±1% for 6MV photon with a 60 degree wedge. Conclusion: Automated output factor measurements can save time by 40% when compared with conventional manual approach. This work laid ground for further improvement for the automation of Linac commissioning.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Automated Work Packages: Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Industry

The need to move conventional paper-based work packages into an electronic state motivated the development of a large span of electronic work package forms that ranged from simple Portable Document Format (PDF) files to adaptive and intelligent electronic forms. In parallel to this development, the Department of Energy Light Water Reactor Sustainability Program (LWRS) initiated the automated work package as a pilot project to evaluate implementing state of the art automation techniques into the work package process to improve the economic and safety of the work process. Through a multiple year’s effort, the automated work package project have developed a vision of the future work package that relies on automation in all critical and human factor challenging tasks. The vision identified gaps in the work process, the means to automate them, and evaluated the implementation, feasibility and benefits of these means. This was conducted through continues engagement with the nuclear power industry. The aim of this report is to study the potential of three automation technologies, which have been advancing in various industries, in the current work process of nuclear power plants. The study is to determine the feasibility and benefits of incorporating the technologies and determine potential gaps, if any, that need to be addressed to facilitate deployment of the studied technologies. The three automation technologies identified for this effort are ultra-high frequency (UHF) radio frequency identification (RFID), Bluetooth low energy (BLE) beacons, and video monitoring and recording. As part of this effort, the Idaho National Laboratory (INL) collaborated with Xcel Energy Inc. to evaluate these technologies. During the research and development scope of the effort, INL engaged Xcel Energy Inc. periodically and exchanged valuable insight on the means to implement these technologies in a nuclear power plant. Multiple pilot prototypes were developed and tested in a user study conducted at Xcel Energy Inc. in Minneapolis, Minnesota. The outcome of this effort resulted in significant findings that included the detailed means to custom fit the technologies to fit the nuclear power industry need, and identifying and evaluating several applications of high economic or safety potential. The limitations and obstacles that could impact deployment of the technologies were also identified, and the means of how to address these limitations and obstacles were studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗

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 NTRS2017

Remotely Piloted Aircraft Systems Panel (RPASP) Working Paper: Autonomy and Automation

A significant level of debate and confusion has surrounded the meaning of the terms "autonomy" and "automation". Automation is a multi-dimensional concept, and we propose that RPAS automation should be described with reference to the specific system and task that has been automated, the context in which the automation functions, and other relevant dimensions. In this paper, we present a definition of "automation". We recommend that autonomy and autonomous operations are out of the scope of the RPAS panel. WG7 proposes to develop, in consultation with other workgroups, a taxonomy of "Levels of Automation" for RPAS.

Autonomy↗

DOE OSTI2016

Automated and Semiautomated Segmentation of Rectal Tumor Volumes on Diffusion-Weighted MRI: Can It Replace Manual Volumetry?

Purpose: Diffusion-weighted imaging (DWI) tumor volumetry is promising for rectal cancer response assessment, but an important drawback is that manual per-slice tumor delineation can be highly time consuming. This study investigated whether manual DWI-volumetry can be reproduced using a (semi)automated segmentation approach. Methods and Materials: Seventy-nine patients underwent magnetic resonance imaging (MRI) that included DWI (highest b value [b1000 or b1100]) before and after chemoradiation therapy (CRT). Tumor volumes were assessed on b1000 (or b1100) DWI before and after CRT by means of (1) automated segmentation (by 2 inexperienced readers), (2) semiautomated segmentation (manual adjustment of the volumes obtained by method 1 by 2 radiologists), and (3) manual segmentation (by 2 radiologists); this last assessment served as the reference standard. Intraclass correlation coefficients (ICC) and Dice similarity indices (DSI) were calculated to evaluate agreement between different methods and observers. Measurement times (from a radiologist's perspective) were recorded for each method. Results: Tumor volumes were not significantly different among the 3 methods, either before or after CRT (P=.08 to .92). ICCs compared to manual segmentation were 0.80 to 0.91 and 0.53 to 0.66 before and after CRT, respectively, for the automated segmentation and 0.91 to 0.97 and 0.61 to 0.75, respectively, for the semiautomated method. Interobserver agreement (ICC) pre and post CRT was 0.82 and 0.59 for automated segmentation, 0.91 and 0.73 for semiautomated segmentation, and 0.91 and 0.75 for manual segmentation, respectively. Mean DSI between the automated and semiautomated method were 0.83 and 0.58 pre-CRT and post-CRT, respectively; DSI between the automated and manual segmentation were 0.68 and 0.42 and 0.70 and 0.41 between the semiautomated and manual segmentation, respectively. Median measurement time for the radiologists was 0 seconds (pre- and post-CRT) for the automated method, 41 to 69 seconds (pre-CRT) and 60 to 67 seconds (post-CRT) for the semiautomated method, and 180 to 296 seconds (pre-CRT) and 84 to 91 seconds (post-CRT) for the manual method. Conclusions: DWI volumetry using a semiautomated segmentation approach is promising and a potentially time-saving alternative to manual tumor delineation, particularly for primary tumor volumetry. Once further optimized, it could be a helpful tool for tumor response assessment in rectal cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗