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A general method for identifying function allocation in human-integrated systems is discussed and applied to the conflict detection and resolution function in air traffic control. The method involves creating a top-down, hybrid state model, where either human or automated agents must perform the functions of detecting the current system state, controlling the current system state, detecting the minimum time available for controlling the current system state, and controlling the minimum time available for controlling the current system state. These functions are considered necessary and sufficient. Allocation of the functions between human and automation can then be made based on the relative abilities of the humans and automation with respect to system performance and system safety.

Previous work has been conducted by McRuer [McRuer, 1973] to model the gain and delay of the pilot-aircraft system using classic control theory methods. However, a continuous extraction of gain and delay further enhances the ability to gather valuable, quantitative data to make inferences about human-machine interaction problems that occur on the flight deck. A parameter tracking system, based on McRuer’s crossover model, has been developed to simultaneously and continuously track the gains and delays at the pilot-machine interface with which pilots track particular axes. The values extracted for gain and delay may be indicative of particular human factors issues that are prevalent in the cockpit, such as inattention, complacency, low situational awareness, and high workload. This model has been developed for use in an artificial tracking task, where it has been observed that if gain and delay are allowed to change freely, the model is overfit and not realistic, as it is believed that gain and delay change rarely, though not necessarily slowly. To combat this, one gain/one delay is applied to the system to find time periods where the fit is poor, and these frames of time are then re-evaluated to find a gain/delay value that fits, and this method is applied across all poorly fit time periods to create a well-fit model. This method of modeling is then applied to a realistic flight simulation task for pilots and is intended to evaluate the levels of gain and delay for specific human-machine tasks incurred on the flight deck, and which axis are affected the most in flight.

Past research in procedure following has primarily concentrated on the effect of procedure-related factors on procedure compliance and non-compliance. Non-compliance is generally considered to be uniformly negative, rather than the outcome that results from other factors. However, there is a general consensus that procedures are not designed for all situations, and that non-compliance can improve outcomes under certain situations. It is therefore important to understand procedure following based on outcomes and not only procedure compliance or non-compliance. To that end, a framework and taxonomy for understanding procedure following has been developed that enables researchers to focus on the outcome of following procedures, not simply on compliance and non-compliance.

With its aging population, the United States is under increasing pressure to provide long-term care (LTC) coverage to its citizens and to manage their chronic health conditions. However, the research on LTC transition and utilization modeling remains in its infancy; needless to mention LTC resource allocation and transition pathway optimization. In this paper, we developed a parametric survival model to characterize nursing home (NH) length of stay (LOS), which incorporates information on transition history. In addition, the model addressed issues such as recurrent events and competing risks. To study the effect of covariates on LOS and to ensure the flexibility of the model in evaluating operational-level interventions, we elected to develop an accelerated failure time parametric survival model. We fit the model to care transition data collected from a large cohort of older adults receiving coordinated care in a Midwestern United States urban area. Through our study, we drew the following major conclusions: 1) transition history is a significant factor and a potential predictor of an individual’s LOS in NH; 2) significance of frailty terms indicates that LOS estimates based on data with recurrent transition events can be significantly biased if not accounted for explicitly; and 3) the same clinical covariate can have opposite effects on NH LOS, depending on the destination care setting. Finally, we identified better-suited baseline hazard functions and frailty terms in each survival model from several representative candidates. Findings from our model can aid in operational-level NH care transition and utilization policy development. This paper also serves as the basis for extension into network-wide LTC transition models and utilization simulators. Note to Practitioners —This paper was motivated by the complex problem of characterizing care transitions in an LTC network, based on integrated electronic health records. It exemplifies the beginning of a series of rigors investigations on modeling multisite care transition networks. This line of research has great potential to lead to the development of intelligent decision support systems for LTC capacity planning and transition management, and eventually, empower care organizations to make data-informed management decisions. Furthermore, the empirical aspect of this paper was made possible by the availability of a comprehensive care transition longitudinal data set, at the Regenstrief Institute, constructed from a multiyear follow-up study on an elderly cohort. This cohort was prospectively followed as it moved along a Midwestern United States urban LTC system. This problem is of great interest to population-level LTC policy makers and management of LTC providers. The majority of the existing studies on LTC delivery have relied on cost-effectiveness analysis based on aggregate spending data. Our study, on the other hand, focuses on characterizing time-to-transition event for patients who reside at NH. Such a shift in focus in modeling at an increased level of granularity enhances our ability to evaluate the impact of operational-level interventions on various outcomes of LTC delivery. Finally, the novelty of our study arises from exploring useful transition history patterns to incorporate into the parametric survival model and estimating resource use from censored data. Our research findings highlight the significance of: 1) identifying the most informative time window for incorporation of transition history as a LOS predictor in NH and 2) accounting for bias in transition time estimation arising from an individual tendency to stay longer or shorter in NH through frailty terms incorporated in the parametric survival model.

The linguistic conjecture that a person's knowledge regarding a situation affects some aspects of that person's performance at a task is translated into a mathematical structure. The structure contains a symbolic representation of the conjecture, along with a symbolic definition of what type of knowledge constitutes ‘situation’ knowledge. The structure is applied to a short example to demonstrate its use. The translation of the conjecture into a mathematical structure enables researchers to use a consistent, objective framework for testing hypothesised relationships between one's situation knowledge and performance, as well as enables mathematical tools to be applied to the study of this conjecture.

For analyzing changes in an individual's health over time, this research has developed objective measures for comparing behavioral patterns, including sleep quality and activity scores. These novel measures of behavioral health have provided insight about how sleep debt accumulates after long, extended days, how sleep disruption and recovery from wakefulness occur during the night, and when cross-correlations exist between measures. This data-driven approach to quantifying behavioral patterns is informed by minute-by-minute data from consumer-grade, wrist-worn wearables. In this 8-month longitudinal study, Jawbone UP wristbands and the Jawbone UP API were utilized to collect minute-by-minute data about the behavior of crewmembers participating in a simulated Mars mission. To study the challenges of living and working on the planet Mars, for eight months, these crewmembers were confined to a Mars-like habitat, living in close quarters, isolated from the rest of humanity at a high elevation on Mauna Loa volcano in Hawaii, wearing mock spacesuits while exploring the volcanic terrain, consuming shelf-stable foods, restricted in water usage, relying on solar energy, and delayed in communications with 20-min lag-times for delivering messages to and from the crew. Analyzing the behavior of these astronaut-like individuals has led to the development of objective measures for quantifying sleep patterns, that have potential for contributing to the development of next-generation, smart wearables.

Research highlights an attempt to quantify relative accuracy of the consumer-grade wearable devices.Models were trained to adjust for data collected from Fitbit Device to the equivalent value in terms of the Jawbones measurement.The models are dependent on the intensity of the activity (Magnitude of Measurement) recorded by the devices.High calories-steps correlation suggests consumer grade devices possibly neglect other factors leading to calories count.Considerations for database-design and nomenclature have been suggested based on existing flaws. Differences in data output from two leading devices in the consumer-grade wearables market have been examined, namely Jawbone UP4 and Fitbit Charge HR devices, by comparing measurements that were conducted while participants wore both devices in tandem. Aggregate daily totals of steps and calories were shown to be highly correlated between devices (0.820.93 correlation coefficient for steps and 0.710.85 for calories); however, at the hourly level, differences in data output are evident, especially during hours of vigorous activity. These differences lead to both under- and over-estimation of measures such as hourly step-counts. Heart rate measurement with Jawbone and Fitbit is shown to be significantly different even at the daily level (p-value

A set of studies has been focused on identifying “markers” in aircraft data that are indicative of human factors issues. In this paper we discuss an experiment that investigated if human error is predictable from the error observed from the combined human-machine system. Sixteen pilots flew simulated instrument approaches under varying levels of workload and control augmentation conditions. Operator control lag, gain, delay, and error extent were computed from aircraft lateral path errors. These parameters along with pupil diameter data were analyzed for differences across workload conditions. Main effects for workload were found with respect to all control parameters consistent with the experiment hypotheses, but the effects were very small. Operator delay in responding to errors appeared inversely correlated with workload. Statistically significant differences were also found with respect to error extent ad pupil diameter.

When jetliners fly in the stratosphere, their emissions tend to be longer-lived and therefore have greater environmental impact. Since the altitude of the tropopause is not consistent and can be as low as 23,000 ft., cruising flights may have a great chance to fly into the stratosphere. In this paper, we present a simple and rapid method to estimate the extent of US commercial passenger and cargo flight that currently occurs in the stratosphere, based on publicly available historical data from 2008 to 2012. We model the vertical profile of a flight and compare it with the height of the tropopause along its route. Our analysis covers 78% of the total travelled distance reported by the United States Bureau of Transportation Statistics, and shows that these flights burnt ∼11 million tons of fuel annually, or ∼31% of cruise fuel, in the stratosphere between 2008 and 2012. Our results also show that the chance of flying into stratosphere varies by area, but flights within the contiguous United States tend to stay below the stratosphere. Moreover, the stratosphere fuel burn of Asia-US flights may be significantly reduced by taking jet stream routes.

A southeast Asian air traffic control system will be undergoing a large procedural change in the next year, moving from paper flights strips to a stripless flight management system. This is the largest technological change the company has undergone in recent history, and they expressed desire to develop a training program, and this research works to identify topics to for training to directly address the concerns and needs of staff members to help ensure a smoother transition period. Open-ended questionnaires are utilized to evaluate what thoughts, concerns, and attitudes staff members have for their current system and procedures as well as their feelings towards the proposed stripless flight management system. Lexical analysis is applied to the questionnaire results to determine which topics staff members most frequently mention. The ten most frequently used words throughout the questionnaires are training/practice, equipment, easy, traffic, knowledge, compatibility, reliability, coordination, staff, and radar. These results are then used as criteria for analysis using the analytical hierarchy process (AHP), where staff members are presented with a survey to rank which criteria are most important, relative to the other criteria, in helping them perform their job tasks safely. The AHP surveys, which are still pending, are analyzed to assign a weight to each criterion, therefore mathematically assigning importance. The criteria chosen as most important by the experts (controllers and staff members) will be utilized as key points in the development of the training program for the new stripless system. A smoother training and transition period for the new system is expected by directly addressing the staff members’ thoughts and concerns up front as found through the questionnaires and AHP analysis.

A study was conducted to identify potential markers for low- and high workload within continuous control data. These markers include derived parameters, such as error, as well as modeled parameters. With respect to the modeled parameters, a parameter tracking system has been developed for modeling the gain and delay with which pilots respond to deviations from desired state values, such as altitude, course, and speed. The system models these parameters based on the McRuer crossover model where the mean-squared error between the modeled parameters and the actual values has been minimized. Several potentially distinguishing markers for identifying excessively low- and high workload levels were found, including measures of error duration, extent, and modeled parameters of operator gain and delay.

In this work arrival traffic following a continuous descent approach profile into the Hartsfield-Jackson Atlanta International Airport was simulated based on actual recorded traffic data. The fuel ...

Two experiments were conducted to (1) test and quantify the effect of an adaptive function allocation system on human performance under different combinations of trigger type (heart rate vs. performance-based) and function allocation adaptation strategy (complete reallocation, partial reallocation, partial transformation) and (2) to determine if the adaptive function allocation system continues to actively change the level of automation over relatively long periods of time (30 min). It was found that the adaptive function allocation system improves primary task performance by, on average, 6% and does not improve secondary task performance. In addition, the level of automation did not stabilize over the 30 min, suggesting the adaptive function a system continues to be relevant even over longer periods of time. Lastly, the study found that the use of heart rate as a trigger mechanism resulted in many more reallocations of function than a performance-based measure. Relevance to industry These findings provide guidance for industry on the extent of performance improvement that can be expected from adaptive function allocation systems, and design choices that may maximize that benefit.

Multiple-view visualisations offer several advantages, such as providing different perspectives on the data. However, there are also associated cognitive costs, including the load on working memory and the effort required for comparison. Furthermore, little perception-based research has been conducted, with few answers to questions such as what tasks multiple views are best used for. Since task performance can be limited by visual attention and working memory, this article investigates how different tasks and their respective loads on attention and working memory affect the usability of two different multiple-view visualisations, namely sequential and simultaneous views. In Study 1, the effects when attention was loaded were studied, where users performed a real-time monitoring task. The results suggest that the divided attention problem was an issue with both view types, but design issues apparent with the simultaneous view were not issues with the sequential view. In Study 2, the effects when working memory was loaded were studied, where users made comparisons of different object sets. The results support the previous work on visual-and memory-based comparisons, i.e. the simultaneous view was more useful than the sequential view. The outcomes from both studies illustrate the importance of understanding how different tasks and their impact on attention and working memory can influence the usability of multiple-view visualisations.

A IR transportation system inefficiencies are found when air traffic demand exceeds system capacity. The resulting flight delays thus increase operating costs of airlines, air traffic controllers’ workload, and the probability of passengers missing connecting flights. Moreover, the air traffic demand is expected to continue its rapid growth in the future. The Federal Aviation Administration estimated in 2007 that the number of passengers is projected to increase by an average of 3% every year until 2025. Most of the traffic demand increase will occur in metropolitan areas where there are two or more large airports. The Joint Planning and Development Office defines this kind of region, with a group of two ormore nearby airports for which the arrival and departure operations are highly interdependent, as a metroplex. The New York Metroplex [N90 terminal radar approach control facilities (TRACON)], for example, consists of John F. Kennedy International Airport (JFK), LaGuardia airport (LGA), and Newark Liberty International Airport (EWR), as well as several smaller airports. The study in [1] shows that the traffic in most metroplexes has increased significantly over the past years, and the N90 metroplex has the heaviest traffic demand. Future traffic growth will put current facilities under extreme pressure. Therefore, determining how to reduce delays at metroplexes is critical. The metroplex phenomenon was first studied by Atkins in the San Francisco Bay area and N90 [2]. It was shown that metroplex phenomena would affect the total capacity of the metroplex airport system. In [3],Atkins andEngelland presented ametroplex definition based on several measurable dimensions and proposed an initial framework to study the nature of metroplexes. Wang et al. [4] and Donohue et al. [5] studied the airports in N90 early in 2008, and they considered the status of each airport in terms of the markets served, seat capacity, delays, and other features. McClain and Clarke [6] designed the metric for metroplex clustering analysis. The dependencies and impacts of the three major airports (JFK, LGA, andEWR) in theN90metroplexwere analyzed byAyyalasomayajula and DeLaurentis in [7,8], where several metrics and models were developed to provide insights for planners to formulate policies and strategies that streamline metroplex operations and mitigate delays. Although the metroplex concept and its corresponding metrics have been studied by a few researchers, there are very few of them discussing how to increase the metroplex efficiency and reduce the total delay. In this Note, an integrated flexible flight operation simulation platform is introduced, which consists of multiple functional modules such as routing, scheduling, flexible flight selection, and flexible flight candidate plan estimation. Particularly, the routing module is described in detail. The metroplex routing algorithms are implemented by constructing a network data structure from the waypoints (navigational aids, arrival fixes, metering fixes, etc.) and jet routes. Two algorithms are applied with and without the en route traffic congestion constraint, respectively. To the authors’ best knowledge, this work is among the very first integrations of the complete flexible flight operation simulation platform with multiple well-developed NASAand university-developed tools. The rest of this Note is organized as follows. The second section, Sec. II, introduces the concepts of the metroplex and flexible flights. The overview of the integration platform and its functional modules is also presented. Section III shows how the network data structure is established and themetroplex routing algorithms with/without traffic congestion constraints are applied. Section IV shows the simulation results of the N90 metroplex, and Sec. V concludes the Note.

User interface design of nowadays safety-critical human-machine systems has a significant impact on human operator situation awareness (SA). SA is composed of three levels including the perception (level 1), comprehension (level 2) and projection (level 3) of information. A significant part of accidents can be attributed to level 1 error. This means that human operators have problems to satisfy their information demand with supplied information during task performance. While thoroughly checking user interface designs for information gaps is a standard in professional system design it is a time consuming and error prone process. In this paper we introduce an information gap model, which allows investigation of inconsistencies between information supply and demand. We present a method to detect information gaps and assess the fitness between information supply and demand. The method can be executed semi-automatically. We show the method’s implementation into an integrated system modelling environment and demonstrate the application with an autopilot component in a course change task on a ship bridge. We performed an expert evaluation with maritime system engineers and a human factors ergonomist to estimate the applicability, benefits and shortcomings of the method. Overall, the evaluation results are promising and warrant further research of the method.