The Impact of Automation and Stress on Human Performance in UAV Operation

The United States Air Force (USAF) has increasing needs for unmanned aerial vehicle (UAV) operators. Automation may enable a single operator to manage multiple UAVs at the same time. Multi-UAV operation may require a unique set of skills and the need for new operators calls for targeting new populations for recruitment. The objective of this research is to develop a simulation environment for studying the role of individual differences in UAV operation under different task configurations and investigate predictors of performance and stress. Primarily, the study examined the impact of levels of automation (LOAs), as well as task demands, on task performance, stress and operator reliance on automation. Two intermediate LOAs were employed for two surveillance tasks included in the simulation of UAV operation. Task demand was manipulated via the high and low frequency of events associated with additional tasks included in the simulation. The task demand and LOA manipulations influenced task performance generally as expected. The task demand manipulations elicited higher subjective distress and workload. LOAs did not affect operator workload but affected reliance behavior. Also, this study examined the role of individual differences in simulated UAV operation. A variety of individual difference factors were associated with task performance and with subjective stress response. Video gaming experience was linked to lower distress and better performance, suggesting possible transfer of skills. Some gender differences were revealed in stress response, task performance, but all the gender effects became insignificant with gaming experience controlled. Generally, the effects of personality were consistent with previous studies, except some novel findings with the performance metrics. Additionally, task demand was found to moderate the influence of personality factors on stress response and performance metrics. Specifically, conscientiousness was associated with higher subjective engagement and performance when demands were higher. This study supports future research which aims to improve the dynamic interfaces in UAV operation, optimize operator reliance on automation, and identify individuals with the highest aptitude for multi-UAV control

Boredom and Distraction in Multiple Unmanned Vehicle Supervisory Control

Operators currently controlling Unmanned Aerial Vehicles report significant boredom, and such systems will likely become more automated in the future. Similar problems are found in process control, commercial aviation, and medical settings. To examine the effect of boredom in such settings, a long duration low task load experiment was conducted. Three low task load levels requiring operator input every 10, 20, or 30 minutes were tested in a our-hour study using a multiple unmanned vehicle simulation environment that leverages decentralized algorithms for sometimes imperfect vehicle scheduling. Reaction times to system-generated events generally decreased across the four hours, as did participants’ ability to maintain directed attention. Overall, participants spent almost half of the time in a distracted state. The top performer spent the majority of time in directed and divided attention states. Unexpectedly, the second-best participant, only 1% worse than the top performer, was distracted almost one third of the experiment, but exhibited a periodic switching strategy, allowing him to pay just enough attention to assist the automation when needed. Indeed, four of the five top performers were distracted more than one-third of the time. These findings suggest that distraction due to boring, low task load environments can be effectively managed through efficient attention switching. Future work is needed to determine optimal frequency and duration of attention state switches given various exogenous attributes, as well as individual variability. These findings have implications for the design of and personnel selection for supervisory control systems where operators monitor highly automated systems for long durations with only occasional or rare input.This work was supported by Aurora Flight Sciences under the ONR Science of Autonomy program as well as the Office of Naval Research (ONR) under Code 34 and MURI [grant number N00014-08-C-070]

Personalidad, estrés y resiliencia: Perspectiva multifactorial de la ciencia cognitiva

Personality traits are consistently correlated with various indices of acute psychological stress response, including negative emotions and performance impairment. However, resilience is a complex personal characteristic with multiple neural and psychological roots. This article advocates a multifactorial approach to understanding resilience that recognizes the complexity of the topic both empirically and theoretically. The Trait-Stressor-Outcome (TSO) framework for organizing empirical data recognizes the multiplicity of traits, stressors and outcome metrics that may moderate stress response. Research requires a fine-grained data collection approach that discriminates multiple stress factors. Also, multiple layers of theory are necessary to explain individual differences in stress response, including biases in neural functioning, attentional processing, as well as styles of coping and emotion-regulation. Cognitive science differentiates multiple levels of explanation and allows for the integration of mechanisms at multiple levels of abstraction from the neural substrate. We illustrate the application of the multifactorial approach to collecting interpreting data on operator stress resulting from interaction with technology.Rasgos de la personalidad están correlacionados coherente con varios índices de la repuesta psicológica al estrés agudo, incluidas las emociones negativas y el deterioro del rendimiento. Sin embargo, resiliencia es una característica personal compleja con múltiples raíces neurales y psicológicas. Para entender resiliencia, este artículo aboga por el enfoque multifactorial que entiende su complejidad tanto empírica como teórica. El marco rasgo-estresor-resultado (RES) para organizar datos empíricos reconoce la multiplicidad de métricas de rasgos, estresores y resultados que podrían moderar respuesta al estrés. La investigación requiere un enfoque de recolección de datos finamente elaborados que distingue factores múltiples de estrés. Además, son necesarios niveles múltiples de teoría para explicar diferencias individuales en la respuesta al estrés, incluidos los sesgos en el funcionamiento neural, procesos de atención, tanto como los estilos de afrontamiento y regulación de emociones. Ciencia cognitiva diferencia niveles múltiples de explicación y permite la integración de mecanismos a niveles múltiples de abstracción del sustrato neural. Demostramos la aplicación del enfoque multifactorial para la recolección de datos interpretativos sobre el estrés laboral que proviene de la interacción con la tecnología

Friend/foe Identification Accuracy And Shooting Performance: Effects Of Prior Task Loading And Time Pressure

The current dismounted soldier and the soldier of the future will be loaded with more information processing tasks while they perform shooting tasks. It is conceivable that some increased level of cognitive tasking may be performed simultaneously with required shooting tasks. The effect of cognitive load on shooting performance has been previously examined (Scribner and Harper, 2001). This study concentrated on the effect of various cognitive workload demands on a friend-foe discrimination shooting task in a single- and dual-task scenario. In light of this, it is imperative that the soldier not be overburdened mentally, which may result in decreased survivability and lethality. Specifically, this study was designed to examine the ability of the soldier to perform friend-foe target discrimination and shooting accuracy, with varying target exposure times, friendly target signatures, and varying cognitive load demands (working memory recall task). Using the Small Arms Simulator Testbed (SAST) we examined the effects of manipulations of working memory load and sustained information transfer, on shooting performance (as measured by target acquisition and friend/foe discrimination indices). Additionally, we investigated subjective measures of workload and stress. A secondary task, administered aurally, was given to subjects to attend to while they performed shooting (friend/foe discrimination task) scenarios: working memory recall task. Each type of task consisted of three levels of difficulty. Analysis of variance revealed significant differences for the memory recall task during shooting and non-shooting conditions. Furthermore, results showed that workload increased as a function of task demand, with associated decreases in shooting performance

The use of multi-attribute task battery in mental workload studies: A scoping review

Multi-Attribute Task Battery (MATB) is a software that has been arguably utilized in many ergonomics/human factors studies, including in the topic of mental workload. However, the use of this well-known program in diverse investigations has not yet been systematically tracked. Furthermore, it may be argued that a critical appraisal of MATB is urgently needed so that future researchers and users can take several crucial factors into account when planning a study or experiment using MATB. The aim of this paper is to comprehensively identify and review the use of MATB software in published studies. This aim might be accomplished by achieving two goals: (1) systematic discovery of published papers in literature databases and (2) categorization of research according to pertinent topics. In this paper, thirty-one articles were included for analysis after carefully screening for their eligibility. Our scoping review finds that MATB is a beneficial program for creating multitasking environments in general, with aviation being the area where it has been used the most. The program was also extensively used for studies on mental workload, especially by producing various stimuli that ultimately result in varying degrees of task demand or difficulty. Moreover, to successfully use MATB, researchers must be aware of a few operational issues and criticisms

Differentiating Active And Passive Fatigue States With The Use Of Electroencephalography

With advances in automation technology, it is becoming essential to understand how automation affects human operators. A concern for the implementation of automation technology is the interactive effects it has with operator cognitive fatigue. Desmond and Hancock (2001) proposed that two types of fatigue can arise depending on the nature of the task: active and passive. Active fatigue results when operators must make constant perceptual-motor adjustments during high task demands, while passive fatigue results from operators executing little or no perceptual-motor adjustments during low task demands, similar to when automation is employed. The purpose of this study was to use electroencephalographic (EEG) indices of workload, engagement, and a candidate marker of strain under fatigue in conjunction with performance and subjective measures to differentiate active and passive fatigue states. Participants (N = 84) performed a generalized flight simulator for 62 min either under active, passive, or control conditions. Passive fatigue was characterized by reduced EEG engagement and initially elevated and stable ratios of Fz theta to POz alpha power compared to active fatigue. Subjective measure results indicated that passive fatigue was characterized by reduced ratings of alertness and workload compared to active fatigue. No performance differences were observed between fatigue conditions; however, an overall speed-accuracy trade-off was observed from pre to post fatigue induction. This study demonstrated that different fatigue states produce different effects on EEG indices. These results have potential applications for developing augmented cognition technologies that deliver appropriate fatigue countermeasures in automated operational environments

MODEL-BASED ASSESSMENT OF ADAPTIVE AUTOMATION’S UNINTENDED CONSEQUENCES

Recent technological advances require development of human-centered principles for their inclusion into complex systems. While such programs incorporate revolutionary hardware and software advances, there is a necessary space for including human operator design considerations, such as cognitive workload. As technologies mature, it is essential to understand the impacts that these emerging systems will have on cognitive workload. Adaptive automation is a solution that seeks to manage cognitive workload at optimal levels. Human performance modeling shows potential for modeling the effects of adaptive automation on cognitive workload. However, the introduction of adaptive automation into a system can also present unintended negative consequences to an operator. This dissertation investigated potential negative unintended consequences of adaptive automation through the development of human performance models of a multi-tasking simulation. One hundred twenty participants were enrolled in three human-in-the-loop experimental studies (forty participants each) that collected objective and subjective surrogate measures of cognitive workload to validate the models. Results from this research indicate that there are residual increases in operator workload after transitions in system states between manual and automatic control of a task that need to be included in human performance models and in system design considerations.Approved for public release. Distribution is unlimited.Lieutenant Colonel, United States ArmyCommanding Officer, U.S. Army Combat Capabilities Development Command, Aviation and Missile Center Agency, Redstone Arsenal, Alabama 35898-500

Perceived connections between information and communication technology use and mental symptoms among young adults - a qualitative study

<p>Abstract</p> <p>Background</p> <p>Prospective associations have been found between high use of information and communication technology (ICT) and reported mental symptoms among young adult university students, but the causal mechanisms are unclear. Our aim was to explore possible explanations for associations between high ICT use and symptoms of depression, sleep disorders, and stress among young adults in order to propose a model of possible pathways to mental health effects that can be tested epidemiologically.</p> <p>Methods</p> <p>We conducted a qualitative interview study with 16 women and 16 men (21-28 years), recruited from a cohort of university students on the basis of reporting high computer (n = 28) or mobile phone (n = 20) use at baseline and reporting mental symptoms at the one-year follow-up. Semi-structured interviews were performed, with open-ended questions about possible connections between the use of computers and mobile phones, and stress, depression, and sleep disturbances. The interview data were analyzed with qualitative content analysis and summarized in a model.</p> <p>Results</p> <p>Central factors appearing to explain high quantitative ICT use were personal dependency, and demands for achievement and availability originating from the domains of work, study, social life, and individual aspirations. Consequences included mental overload, neglect of other activities and personal needs, time pressure, role conflicts, guilt feelings, social isolation, physical symptoms, worry about electromagnetic radiation, and economic problems. Qualitative aspects (destructive communication and information) were also reported, with consequences including vulnerability, misunderstandings, altered values, and feelings of inadequacy. User problems were a source of frustration. Altered ICT use as an effect of mental symptoms was reported, as well as possible positive effects of ICT on mental health.</p> <p>Conclusions</p> <p>The concepts and ideas of the young adults with high ICT use and mental symptoms generated a model of possible paths for associations between ICT exposure and mental symptoms. Demands for achievement and availability as well as personal dependency were major causes of high ICT exposure but also direct sources of stress and mental symptoms. The proposed model shows that factors in different domains may have an impact and should be considered in epidemiological and intervention studies.</p

Attentional Narrowing: Triggering, Detecting and Overcoming a Threat to Safety.

In complex safety-critical domains, such as aviation or medicine, considerable multitasking requirements and attentional demands are imposed on operators who may, during off-nominal events, also experience high levels of anxiety. High task load and anxiety can trigger attentional narrowing – an involuntary reduction in the range of cues that can be utilized by an operator. As evidenced by numerous accidents, attentional narrowing is a highly undesirable and potentially dangerous state as it hampers information gathering, reasoning, and problem solving. However, because the problem is difficult to reproduce in controlled environments, little is known about its triggers, markers and possible countermeasures. Therefore, the goals of this dissertation were to (1) identify reliable triggers of attentional narrowing in controlled laboratory settings, (2) identify real-time markers of attentional narrowing that can also distinguish that phenomenon from focused attention – another state of reduced attentional field that, contrary to attentional narrowing, is deliberate and often desirable, (3) develop and test display designs that help overcome the narrowing of the attentional field. Based on a series of experiments in the context of a visual search task and a multi-tasking environment, novel unsolvable problems were identified as the most reliable trigger of attentional narrowing. Eye tracking was used successfully to detect and trace the phenomenon. Specifically, three eye tracking metrics emerged as promising markers of attentional narrowing: (1) the percentage of fixations, (2) dwell duration and (3) fixation duration in the display area where the novel problem was presented. These metrics were used to develop an algorithm capable of detecting attentional narrowing in real time and distinguishing it from focused attention. A command display (as opposed to status) was shown to support participants in broadening their attentional field and improving their time sharing performance. This dissertation contributes to the knowledge base in attentional narrowing and, more generally, attention management. A novel eye tracking based technique for detecting the attentional state and a promising countermeasure to the problem were developed. Overall, the findings from this research contribute to improved safety and performance in a range of complex high-risk domains.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135773/1/jprinet_1.pd