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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.

Bailey, Nathan R.↗
NASA NTRS1991

Human-centered aircraft automation: A concept and guidelines

Aircraft automation is examined and its effects on flight crews. Generic guidelines are proposed for the design and use of automation in transport aircraft, in the hope of stimulating increased and more effective dialogue among designers of automated cockpits, purchasers of automated aircraft, and the pilots who must fly those aircraft in line operations. The goal is to explore the means whereby automation may be a maximally effective tool or resource for pilots without compromising human authority and with an increase in system safety. After definition of the domain of the aircraft pilot and brief discussion of the history of aircraft automation, a concept of human centered automation is presented and discussed. Automated devices are categorized as a control automation, information automation, and management automation. The environment and context of aircraft automation are then considered, followed by thoughts on the likely future of automation of that category.

Billings, Charles E.↗
NASA NTRS1997

Automation-induced monitoring inefficiency: role of display location

Operators can be poor monitors of automation if they are engaged concurrently in other tasks. However, in previous studies of this phenomenon the automated task was always presented in the periphery, away from the primary manual tasks that were centrally displayed. In this study we examined whether centrally locating an automated task would boost monitoring performance during a flight-simulation task consisting of system monitoring, tracking and fuel resource management sub-tasks. Twelve nonpilot subjects were required to perform the tracking and fuel management tasks manually while watching the automated system monitoring task for occasional failures. The automation reliability was constant at 87.5% for six subjects and variable (alternating between 87.5% and 56.25%) for the other six subjects. Each subject completed four 30 min sessions over a period of 2 days. In each automation reliability condition the automation routine was disabled for the last 20 min of the fourth session in order to simulate catastrophic automation failure (0 % reliability). Monitoring for automation failure was inefficient when automation reliability was constant but not when it varied over time, replicating previous results. Furthermore, there was no evidence of resource or speed accuracy trade-off between tasks. Thus, automation-induced failures of monitoring cannot be prevented by centrally locating the automated task.

Automation↗
NASA NTRS1996

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis↗
NASA NTRS1993

Performance consequences of automation-induced 'complacency'

The effect of variations in the reliability of an automated monitoring system on human operator detection of automation failures was examined in two experiments. For four 30-min sessions, 40 subjects performed an IBM PC-based flight simulation that included manual tracking and fuel-management tasks, as well as a system-monitoring task that was under automation control. Automation reliability - the percentage of system malfunctions detected by the automation routine - either remained constant at a low or high level over time or alternated every 10 min from low to high. Operator detection of automation failures was substantially worse for constant-reliability than for variable-reliability automation after about 20 min under automation control, indicating that the former condition induced 'complacency'. When system monitoring was the only task, detection was very efficient and was unaffected by variations in automation reliability. The results provide the first empirical evidence of the performance consequences of automation-induced 'complacency'. We relate findings to operator attitudes toward automation and discuss implications for cockpit automation design.

Parasuraman, Raja↗
NASA NTRS2001

Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.

Breed, Julie↗
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 NTRS2005

Robotic and Human-Tended Collaborative Drilling Automation for Subsurface Exploration

Future in-situ lunar/martian resource utilization and characterization, as well as the scientific search for life on Mars, will require access to the subsurface and hence drilling. Drilling on Earth is hard - an art form more than an engineering discipline. Human operators listen and feel drill string vibrations coming from kilometers underground. Abundant mass and energy make it possible for terrestrial drilling to employ brute-force approaches to failure recovery and system performance issues. Space drilling will require intelligent and autonomous systems for robotic exploration and to support human exploration. Eventual in-situ resource utilization will require deep drilling with probable human-tended operation of large-bore drills, but initial lunar subsurface exploration and near-term ISRU will be accomplished with lightweight, rover-deployable or standalone drills capable of penetrating a few tens of meters in depth. These lightweight exploration drills have a direct counterpart in terrestrial prospecting and ore-body location, and will be designed to operate either human-tended or automated. NASA and industry now are acquiring experience in developing and building low-mass automated planetary prototype drills to design and build a pre-flight lunar prototype targeted for 2011-12 flight opportunities. A successful system will include development of drilling hardware, and automated control software to operate it safely and effectively. This includes control of the drilling hardware, state estimation of both the hardware and the lithography being drilled and state of the hole, and potentially planning and scheduling software suitable for uncertain situations such as drilling. Given that Humans on the Moon or Mars are unlikely to be able to spend protracted EVA periods at a drill site, both human-tended and robotic access to planetary subsurfaces will require some degree of standalone, autonomous drilling capability. Human-robotic coordination will be important, either between a robotic drill and humans on Earth, or a human-tended drill and its visiting crew. The Mars Analog Rio Tinto Experiment (MARTE) is a current project that studies and simulates the remote science operations between an automated drill in Spain and a distant, distributed human science team. The Drilling Automation for Mars Exploration (DAME) project, by contrast: is developing and testing standalone automation at a lunar/martian impact crater analog site in Arctic Canada. The drill hardware in both projects is a hardened, evolved version of the Advanced Deep Drill (ADD) developed by Honeybee Robotics for the Mars Subsurface Program. The current ADD is capable of 20m, and the DAME project is developing diagnostic and executive software for hands-off surface operations of the evolved version of this drill. The current drill automation architecture being developed by NASA and tested in 2004-06 at analog sites in the Arctic and Spain will add downhole diagnosis of different strata, bit wear detection, and dynamic replanning capabilities when unexpected failures or drilling conditions are discovered in conjunction with simulated mission operations and remote science planning. The most important determinant of future 1unar and martian drilling automation and staffing requirements will be the actual performance of automated prototype drilling hardware systems in field trials in simulated mission operations. It is difficult to accurately predict the level of automation and human interaction that will be needed for a lunar-deployed drill without first having extensive experience with the robotic control of prototype drill systems under realistic analog field conditions. Drill-specific failure modes and software design flaws will become most apparent at this stage. DAME will develop and test drill automation software and hardware under stressful operating conditions during several planned field campaigns. Initial results from summer 2004 tests show seven identifi distinct failure modes of the drill: cuttings-removal issues with low-power drilling into permafrost, and successful steps at executive control and initial automation.

Glass, Brian↗
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 NTRS1995

Pilot opinions on high level flight deck automation issues: Toward the development of a design philosophy

There has been much concern in recent years about the rapid increase in automation on commercial flight decks. The survey was composed of three major sections. The first section asked pilots to rate different automation components that exist on the latest commercial aircraft regarding their obtrusiveness and the attention and effort required in using them. The second section addressed general 'automation philosophy' issues. The third section focused on issues related to levels and amount of automation. The results indicate that pilots of advanced aircraft like their automation, use it, and would welcome more automation. However, they also believe that automation has many disadvantages, especially fully autonomous automation. They want their automation to be simple and reliable and to produce predictable results. The biggest needs for higher levels of automation were in pre-flight, communication, systems management, and task management functions, planning as well as response tasks, and high workload situations. There is an irony and a challenge in the implications of these findings. On the one hand pilots would like new automation to be simple and reliable, but they need it to support the most complex part of the job--managing and planning tasks in high workload situations.

Tenney, Yvette J.↗
NASA NTRS2009

Effects of Automation Types on Air Traffic Controller Situation Awareness and Performance

The Joint Planning and Development Office has proposed the introduction of automated systems to help air traffic controllers handle the increasing volume of air traffic in the next two decades (JPDO, 2007). Because fully automated systems leave operators out of the decision-making loop (e.g., Billings, 1991), it is important to determine the right level and type of automation that will keep air traffic controllers in the loop. This study examined the differences in the situation awareness (SA) and collision detection performance of individuals when they worked with information acquisition, information analysis, decision and action selection and action implementation automation to control air traffic (Parasuraman, Sheridan, & Wickens, 2000). When the automation was unreliable, the time taken to detect an upcoming collision was significantly longer for all the automation types compared with the information acquisition automation. This poor performance following automation failure was mediated by SA, with lower SA yielding poor performance. Thus, the costs associated with automation failure are greater when automation is applied to higher order stages of information processing. Results have practical implications for automation design and development of SA training programs.

Sethumadhavan, A.↗
NASA NTRS2012

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014. The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such a comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass, ground operations can still reduce mission costs through smaller staffing of operators and limiting their working hours. The challenge, then, for the SMAP GDS engineering team, is to formulate an automated operations strategy--and corresponding system architecture -- to minimize operator intervention during routine operations, while balancing the development costs associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS -- NASA's AMMOS Mission Data Processing and Control System (AMPCS) -- provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

soil moisture↗
NASA NTRS2012

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014.[double dagger] The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass ground operations can still reduce mission cost through smaller staffing of operators and limited work hours. The challenge, then, for the SMAP GDS engineering team is to formulate an automated operations strategy--and corresponding system architecture--to minimize operator intervention during operations, while balancing the development cost associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS--NASA's AMMOS Mission Data Processing and Control System (AMPCS)--provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

remote-sensing↗
NASA NTRS2018

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗
NASA NTRS2002

Automated fault-management in a simulated spaceflight micro-world

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

NASA Discipline Space Human Factors↗
NASA NTRS2014

Controller Inhibition of Automated Conflict Resolutions in a Maximum NextGen Condition

With the continued projection of increases in air traffic density, operations in the National Airspace System are expected to exceed human capabilities in the near future. In order to address the bottleneck of human workload capacity, highly automated safety-critical systems are under development to support air traffic controllers. A human-in-the-loop experiment examined controllers transition through four NextGen automation stages: Current-Day, Minimum, Moderate, and Maximum. Maximum NextGen simulated a fully automated environment where the automation was responsible for detecting and resolving conflicts within simulation parameters in high-density airspace. By allocating these tasks to the automation, the controllers task changed. The human moved to primarily a supervisory position- typically only regaining control over separation assurance tasks during conflict situations deferred by the automation. While tasks were allocated a-priori between the controller and automated agent, controllers maintained authority to inhibit the automation from interacting with particular aircraft. Preliminary work is complete, where significant differences were found in inhibition frequency between simulation participants. However, the contexts in which the controllers inhibited the automation, and their reasons for doing so, remain unclear. This analysis attempts to identity factors contributing to human controllers inhibition of the automation in the Maximum NextGen condition.

adaptable automation↗
NASA NTRS1989

Space biology initiative program definition review. Trade study 1: Automation costs versus crew utilization

A significant emphasis upon automation within the Space Biology Initiative hardware appears justified in order to conserve crew labor and crew training effort. Two generic forms of automation were identified: automation of data and information handling and decision making, and the automation of material handling, transfer, and processing. The use of automatic data acquisition, expert systems, robots, and machine vision will increase the volume of experiments and quality of results. The automation described may also influence efforts to miniaturize and modularize the large array of SBI hardware identified to date. The cost and benefit model developed appears to be a useful guideline for SBI equipment specifiers and designers. Additional refinements would enhance the validity of the model. Two NASA automation pilot programs, 'The Principal Investigator in a Box' and 'Rack Mounted Robots' were investigated and found to be quite appropriate for adaptation to the SBI program. There are other in-house NASA efforts that provide technology that may be appropriate for the SBI program. Important data is believed to exist in advanced medical labs throughout the U.S., Japan, and Europe. The information and data processing in medical analysis equipment is highly automated and future trends reveal continued progress in this area. However, automation of material handling and processing has progressed in a limited manner because the medical labs are not affected by the power and space constraints that Space Station medical equipment is faced with. Therefore, NASA's major emphasis in automation will require a lead effort in the automation of material handling to achieve optimal crew utilization.

Jackson, L. Neal↗
NASA NTRS2007

Methodology for Prototyping Increased Levels of Automation for Spacecraft Rendezvous Functions

The Crew Exploration Vehicle necessitates higher levels of automation than previous NASA vehicles, due to program requirements for automation, including Automated Rendezvous and Docking. Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the Crew Exploration Vehicle development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool. This paper develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology is used to evaluate the accuracy of the Function-specific Level of Autonomy and Automation Tool specified levels of automation, via prototyping. Spacecraft rendezvous planning tasks are selected and then prototyped in Matlab using Fuzzy Logic techniques and existing Space Shuttle rendezvous trajectory algorithms.

Hart, Jeremy J.↗