Accounting for the Speed-Accuracy Trade-Off in Quantifying Human-In-The-Loop Error Probabilities

Human-in-the-loop (HITL) simulations cannot collect enough data from human operators to validate estimates of error probabilities for task components. Error rates for tasks have been estimated by using laboratory data for error rates depending on variables such as the cognitive complexity of the task. The limited channel capacity of human operators compels error rates to be strongly related to the time available for the task, the speed-accuracy trade-off. HITL simulations can provide valuable data on the time available for the operator's tasks. We propose that the response times be used in conjunction with measured speed-accuracy curves to estimate the operator error rates contributing to mission failure. Such analyses should be especially important in the estimation of error rates in off-nominal situations

Perceptual learning in parafoveal vision

AbstractThe present study tests the effects of practice on parafoveal vernier and resolution acuity. By measuring task specificity, transfer of training to other retinal locations in the trained eye and transfer of training to the untrained eye, we directly address whether improvement on these tasks is the result of changes in the underlying physiological processes or simply the development of new cognitive strategies. We found that: (1) significant learning can occur for both vernier and resolution acuity in many (but not all) individuals; (2) there were significant individual differences in the degree and time-course of learning: (3) learning transfers to the untrained task; and (4) learning transfers to the other eye particularly when the visual pathway leads to the trained hemisphere. These results suggest that both physiological and cognitive processes contribute to the improvement seen after repetitive practice on these visual tasks

The Insertion of Human Factors Concerns into NextGen Programmatic Decisions

Since the costs of proposed improvements in air traffic management exceed available funding, FAA decision makers must select and prioritize what actually gets implemented. We discuss a set of methods to help forecast operational and human performance issues and benefits before new automation is introduced. This strategy could minimize the impact of politics, assist decision makers in selecting and prioritizing potential improvements, make the process more transparent and strengthen the link between the engineering and human factors domains

The Fine Motor Skills and Cognition Test Batteries: Normative Data and Interdependencies

Fine motor skills and cognitive abilities are major contributors to crew performance on essentially all extravehicular and intra-vehicular activities during spaceflight. It is critical for the crews safety, and for mission productivity, to know if, and when, motor skills or cognitive abilities are compromised so that countermeasures may be introduced. NASA has developed two test batteries to measure and monitor astronaut cognitive and fine motor skills. The Cognition Test Battery contains 10 sub-tests that assess cognitive behaviors ranging from low level visual perception to high level decision-making. The Fine Motor Skills Test Battery contains 4 sub-tests that assess finger dexterity, manual dexterity and wrist-finger speed. This study sought to determine acceptable norms for both batteries in an astronaut-like population and to identify the extent to which fine motor skills contribute to cognitive test scores

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice

NextGen Operational Improvements: Will They Improve Human Performance

Modernization of the National Airspace System depends critically on the development of advanced technology, including cutting-edge automation, controller decision-support tools and integrated on-demand information. The Next Generation Air Transportation System national plan envisions air traffic control tower automation that proposes solutions for seven problems: 1) departure metering, 2) taxi routing, 3) taxi and runway scheduling, 4) departure runway assignments, 5) departure flow management, 6) integrated arrival and departure scheduling and 7) runway configuration management. Government, academia and industry are simultaneously pursuing the development of these capabilities. For each capability, the development process typically begins by assessing its potential benefits, and then progresses to designing preliminary versions of the tool, followed by testing the tool’s strengths and weaknesses using computational modeling, human-in-the-loop simulation and/or field tests. We compiled research studies of the tools, assessed the methodological rigor of the studies and served as referee for partisan conclusions that were sometimes overly optimistic. Here we provide the results of this review

Object detection in a noisy scene

Observers viewed a simulated airport runway landing scene with an obstructing aircraft on the runway and rated the visibility of the obstructing object in varying levels of white fixed-pattern noise. The effect of the noise was compared with the predictions of single and multiple channel discrimination models. Without a contrast masking correction, both models predict almost no effect of the fixed-pattern noise. A global contrast masking correction improves both models ’ predictions, but the predictions are best when the masking correction is based only on the noise contrast (does not include the background image contrast)

Perceived Usefulness of Planned NextGen Capabilities by Air Traffic Control Tower Controllers

The Next Generation Air Transportation System (NextGen) is an ambitious collaborative effort between government agencies and industry to increase the capabilities of the current air traffic system. Under NextGen, tools are being developed to support air traffic controllers in many aspects of their jobs. However, budgetary constraints, unanticipated technological hurdles and other challenges to implementation make it unlikely that every NextGen tool in development will find its way into future air traffic control facilities. Information is needed to prioritize NextGen tool development to ensure that the tools that will provide the most benefit can be implemented in the appropriate facilities. Toward this end, a web-based survey was conducted of 174 air traffic control tower controllers to identify the perceived usefulness of 10 planned NextGen tower capabilities designed to provide or support: departure metering at the ramp, taxi routing, departure runway assignments, departure flow management, runway scheduling, runway configuration management, integrated arrival/departure scheduling, enhanced surveillance, electronic flight data, and tower data communications. Along with brief descriptions of each of the planned capabilities, surveyed tower controllers were asked to indicate the extent to which each capability would help them in their job and affect capacity, efficiency, flexibility, predictability and safety at their airport. Results indicated that different NextGen capabilities were perceived as useful across different tower facilities. Implications for the prioritization of NextGen tool development are discussed

Spatio-Temporal Discrimination Model Predicts Temporal Masking Functions

e present a simplified dual-channel discrimination model with spatio-temporal filters to represent the t s visual system contrast sensitivity, and masking based on local spatio-temporal contrast energy. The contras ensitivity filter parameters of the model were based on previous work. The masking and global sensitivity h t parameters are calibrated to masking data using brief grating target signals masked by a 700 msec grating wit he same spatial parameters. Keywords: video, image quality, masking, vision models, target detection. T 1. INTRODUCTION his work is part of a research program to develop vision models to help display system designers d e evaluate target and display artifact visibility. Here we describe a computationally simply model for the rapi valuation of the visibility of differences in image sequences. An extension of simple models developed for d static images, this spatio-temporal discrimination model provides for local luminance contrast effects an 1, 2, 3 local m..