Simulated Air Traffic Control Task Research Articles

Operator selection for human-automation teaming: The role of manual task skill in predicting automation failure intervention

Humans working in modern work systems are increasingly required to supervise task automation. We examined whether manual aircraft conflict detection skill predicted participants’ ability to respond to conflict detection automation failures in simulated air traffic control. In a conflict discrimination task (to assess manual skill), participants determined whether pairs of aircraft were in conflict or not by judging their relative-arrival time at common intersection points. Then in a simulated air traffic control task, participants supervised automation which either partially or fully detected and resolved conflicts on their behalf. Automation supervision required participants to detect when automation may have failed and effectively intervene. When automation failed, participants who had better manual conflict detection skill were faster and more accurate to intervene. However, a substantial proportion of variance in failure intervention was not explained by manual conflict detection skill, potentially reflecting that future research should consider other cognitive skills underlying automation supervision.

The effect of multi‐tasking training on performance, situation awareness, and workload in simulated air traffic control

AbstractIncreasingly higher demands are being made on the capacity‐limited cognitive capabilities of human operators as they strive to maintain situation awareness (i.e., understanding “what is going on”) and performance in complex tasks. In the current study we asked whether: (a) training administered via a mobile phone‐based app could improve multitasking and (b) improved multitasking in the app would generalize to improved performance and situation awareness in a simulated air traffic control task (ATC). Participants completed the ATC task before and after multiple sessions of app‐based multitasking training or control training. Multitasking on the app improved across training sessions. However, this did not lead to improved performance or situation awareness, or workload reduction, relative to control training on the ATC task. These outcomes indicate that app‐based multitasking training based on repetition of a single training task will not necessarily yield generalizable benefits to human performance in other complex dynamic tasks.

NeuroTracker Multiple Object Tracking Ability Predicts Novice Performance on a Simulated Air Traffic Control Task

ABSTRACT Objective To explore the utility of multiple object tracking (MOT) ability, measured using NeuroTracker, as a predictor of air traffic control (ATC) task performance. Background The perceptual-cognitive abilities required for MOT are also important for ATC performance. The current study provides a novel examination of NeuroTracker’s utility to predict novice performance on a simulated ATC task, relative to two discrete measures of working memory (WM). Method Forty-six participants completed computer-based assessments of MOT ability (NeuroTracker) and WM (Corsi Block Tapping, Automated Operation Span) followed by the simulated ATC task. Regression analyses were performed to determine the associations between ATC task performance and the MOT and WM measures. Results After controlling for age and video game playing, MOT ability significantly predicted more correct detections of conflicts between aircraft, fewer false alarm responses to conflicts, and faster aircraft acceptance and hand-off. When WM measures were included in regressions, MOT was a stronger predictor of performance than WM on those outcomes, and remained a statistically significant predictor of better conflict detection, false alarm response, and hand-off performance. Conclusion The findings demonstrate the relevance of MOT ability to ATC task performance and support the potential utility of NeuroTracker for controller applicant screening and selection. Research is required to validate the findings in larger and more representative samples under more realistic conditions.

Facial Movements as Indicators of Fatigue in Air Traffic Control Tasks

Air Traffic Control is a work that needs sustained vigilance for a certain period. This condition may result in mental fatigue that can lead to errors or incidents. Facial points could be potential indicators of fatigue that can be used in a real work environment. The objective of this research is to identify the parameters of facial points in order to detect fatigue considering correlation and accuracy value. An Experiment laboratory has been used to capture and recognize five facial points around the eyes of 12 participants when doing moderate and high traffic of simulated Air Traffic Control tasks. Six parameters that are related to movement and fixation of the facial points have been analyzed at five facial points. As a result, among 14 parameters-facial points that have a significant correlation to fatigue, only 4 of them at 2 facial points have good accuracy (>70%) in detecting the increase of fatigue level. Decreasing of movement velocity and increasing of fixation duration of points related to head and eyebrow have been found out when fatigue level increased. It can be concluded that some movement and fixation parameters of facial points are promising to be used in fatigue detection in Air Traffic Control tasks. Copyright © 2020 Praise Worthy Prize - All rights reserved.

Indexing Mental Workload During Simulated Air Traffic Control Tasks by Means of Dual Frequency Head Maps.

In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity. Optimal workload conditions are important for assuring employee's health and safety of other persons. This is particularly relevant in safety-critical occupations, such as air traffic control. For measuring mental workload using the EEG, we have developed the method of Dual Frequency Head Maps (DFHM). The method was tested and validated already under laboratory conditions. However, validation of the method regarding reliability and reproducibility of results under realistic settings and real world scenarios was still required. In our study, we examined 21 air traffic controllers during arrival management tasks. Mental workload variations were achieved by simulation scenarios with different number of aircraft and the occurrence of a priority-flight request as an exceptional event. The workload was assessed using the EEG-based DFHM-workload index and instantaneous self-assessment questionnaire. The DFHM-workload index gave stable results with highly significant correlations between scenarios with similar traffic-load conditions (r between 0.671 and 0.809, p ≤ 0.001). For subjects reporting that they experienced workload variation between the different scenarios, the DFHM-workload index yielded significant differences between traffic-load levels and priority-flight request conditions. For subjects who did not report to experience workload variations between the scenarios, the DFHM-workload index did not yield any significant differences for any of the factors. We currently conclude that the DFHM-workload index reveals potential for applications outside the laboratory and yields stable results without retraining of the classifiers neither regarding new subjects nor new tasks.

Cross-task cue utilisation and situational awareness in simulated air traffic control

ObjectiveTo examine the role of cross-task cue utilisation in the acquisition of situational awareness during the initial stages of learning to operate an air traffic control simulation. BackgroundCue-based associations are an important component of situational awareness, a construct that is necessary for skilled process control, where the location, movement, and direction of multiple targets needs to be managed. However, the potential for high levels of situational awareness is difficult to assess in the absence of exposure. Previous research suggests that cross-task cue utilisation predicts the acquisition of feature-event associations that form the basis of situational awareness MethodSixty university students undertook an assessment of cue utilisation in the context of motor vehicle driving and subsequently engaged in an air traffic control simulation task. During the air traffic control simulation task, situational awareness queries were introduced based on the Situation Awareness Global Assessment Test (SAGAT). ResultsThe analyses revealed that participants who demonstrated relatively higher levels of cross-task cue utilisation also demonstrated greater performance on the SAGAT and achieved greater performance during the simulated air traffic control task. ConclusionThe outcomes suggest a relationship between cross-task cue utilisation and situational awareness, particularly at the initial stages of skill acquisition. ApplicationAssessments of cross-task cue utilisation may be used to distinguish the propensity for prospective trainees to acquire the situational awareness necessary for complex, process control tasks such as air traffic control.

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

Effects of Peppermint Odor on Performance and Fatigue in a Simulated Air Traffic Control Task

Effects of Peppermint Odor on Performance and Fatigue in a Simulated Air Traffic Control Task

Benefits of Imperfect Conflict Resolution Advisory Aids for Future Air Traffic Control

The aim of this study was to examine the human-automation interaction issues and the interacting factors in the context of conflict detection and resolution advisory (CRA) systems. The issues of imperfect automation in air traffic control (ATC) have been well documented in previous studies, particularly in conflict-alerting systems. The extent to which the prior findings can be applied to an integrated conflict detection and resolution system in future ATC remains unknown. Twenty-four participants were evenly divided into two groups corresponding to a medium- and a high-traffic density condition, respectively. In each traffic density condition, participants were instructed to perform simulated ATC tasks under four automation conditions, including reliable, unreliable with short time allowance to secondary conflict (TAS), unreliable with long TAS, and manual conditions. Dependent variables accounted for conflict resolution performance, workload, situation awareness, and trust in and dependence on the CRA aid, respectively. Imposing the CRA automation did increase performance and reduce workload as compared with manual performance. The CRA aid did not decrease situation awareness. The benefits of the CRA aid were manifest even when it was imperfectly reliable and were apparent across traffic loads. In the unreliable blocks, trust in the CRA aid was degraded but dependence was not influenced, yet the performance was not adversely affected. The use of CRA aid would benefit ATC operations across traffic densities. CRA aid offers benefits across traffic densities, regardless of its imperfection, as long as its reliability level is set above the threshold of assistance, suggesting its application for future ATC.

The neuroergonomic evaluation of human machine interface design in air traffic control using behavioral and EEG/ERP measures

The Air Traffic Control (ATC) environment is complex and safety-critical. Whilst exchanging information with pilots, controllers must also be alert to visual notifications displayed on the radar screen (e.g., warning which indicates a loss of minimum separation between aircraft). Under the assumption that attentional resources are shared between vision and hearing, the visual interface design may also impact the ability to process these auditory stimuli. Using a simulated ATC task, we compared the behavioral and neural responses to two different visual notification designs—the operational alarm that involves blinking colored “ALRT” displayed around the label of the notified plane (“Color-Blink”), and the more salient alarm involving the same blinking text plus four moving yellow chevrons (“Box-Animation”). Participants performed a concurrent auditory task with the requirement to react to rare pitch tones. P300 from the occurrence of the tones was taken as an indicator of remaining attentional resources. Participants who were presented with the more salient visual design showed better accuracy than the group with the suboptimal operational design. On a physiological level, auditory P300 amplitude in the former group was greater than that observed in the latter group. One potential explanation is that the enhanced visual design freed up attentional resources which, in turn, improved the cerebral processing of the auditory stimuli. These results suggest that P300 amplitude can be used as a valid estimation of the efficiency of interface designs, and of cognitive load more generally.

High Rate of Inattentional Deafness in Simulated Air Traffic Control Tasks

The Air Traffic Control (ATC) environment is complex and safety-critical; operators work in dynamic situations and must make high-risk decisions under stress and temporal pressure. The high perceptual load involved in ATC means that controllers’ attention must be shared between several subtasks, with few or no remaining attentional capacity for processing information that is not related directly to the focal task. In this kind of situation, the likelihood of a controller failing to become aware of an auditory alarm, i.e. inattentional deafness, is high. We designed an ecological ATC thanks to the simulation environment called the “LABY” microworld. Twenty participants were required to guide one (low cognitive load) or two planes (high cognitive load) around a given route, while dealing with visual notifications relating to peripheral aircrafts. During the task, participants were played either standard tones which they were told to ignore, or deviant tones (“the alarm”, probability = 0.20) which they were told to report (20 alarms per scenario). We hypothesized that the detection rate of auditory alarms will decrease with cognitive workload. In order to explore this possibility, Behavioral results showed that 28.8% of alarms were not reported when guiding one plane, and up to 46.2% when guiding two planes (high load). The cognitive load increase led to a reduced visual notification detection rate, but the performance to guiding the central aircrafts was maintained, as well as the reaction times to report auditory alarms when perceived. This high rate of inattentional deafness is essential to further physiological studies on alarm omission in aeronautics, such as ERP or eye movement analysis. Potential applications are related to the integrative online detection and prevention of alarm omission, and the online measurement of workload in ecological situation.

The sustained attention to response task (SART) does not promote mindlessness during vigilance performance.

In this study, we evaluated the validity of the Sustained Attention to Response Task (SART) as a means for promoting mindlessness in vigilance performance. Vigilance tasks typically require observers to respond to critical signals and to withhold responding to neutral events. The SART features the opposite response requirements, which supposedly leads it to promote a mindless, non-thoughtful approach to the vigilance task To test that notion, we compared the SART to the traditional vigilance format (TVF) in terms of diagnostic accuracy assessed through decision theory measures of positive and negative predictive power (PPP and NPP), perceived mental workload indexed by the Multiple Resource Questionnaire, and oculomotor activity reflected in the Nearest Neighbor Index and fixation dwell times. Observers in TVF and SART conditions monitored a video display for collision flight paths in a simulated air traffic control task. Diagnostic accuracy in terms of NPP was high in both format conditions. While PPP was poorer in the SART than in the TVF, that result could be accounted for by a loss of motor control rather than a lack of mindfulness. Identical high levels of workload were generated by the TVF and SART tasks, and observers in both conditions showed similar dynamic scanning of the visual scene. The data indicate that the SART is not an engine of mindlessness. The results challenge the widespread use of the SART to support a model in which mindlessness is considered to be the principal root of detection failures in vigilance.

A sequential sampling account of response bias and speed–accuracy tradeoffs in a conflict detection task.

Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks.

Classifying visual fatigue severity based on neurophysiological signals and psychophysiological ratings

This paper presents a neuroergonomics study of visual fatigue associated with visual display tasks. Symptoms of visual fatigue may include tiredness, headaches, eye soreness, eye aches, discomfort when the eyes are open, difficulties in focusing, and blurred vision. These symptoms can be caused by demands on the visual functions, such as focusing and converging of the eyes. A feed forward artificial neural network (FF-ANN) is used to classify visual fatigue based on the subjects' neurophysiological signals and psychophysiological ratings on a simulated sickness questionnaire (SSQ) scale. Inclusive of all data, a classification accuracy of 83.33 % was obtained (with 70% for training, 15% for validating, and 15% for testing from nine subjects), 90.4% accuracy was obtained using eye response data, 86.78% accuracy with eye and EEG response data, and, 84.93% with eye and hemodynamics response data. The FF-ANN model classifies about 16.7 % and 33.33% of severe and moderate ratings based on medium to difficult simulated air traffic control tasks on the SSQ scale.

Minimizing the disruptive effects of prospective memory in simulated air traffic control.

Prospective memory refers to remembering to perform an intended action in the future. Failures of prospective memory can occur in air traffic control. In two experiments, we examined the utility of external aids for facilitating air traffic management in a simulated air traffic control task with prospective memory requirements. Participants accepted and handed-off aircraft and detected aircraft conflicts. The prospective memory task involved remembering to deviate from a routine operating procedure when accepting target aircraft. External aids that contained details of the prospective memory task appeared and flashed when target aircraft needed acceptance. In Experiment 1, external aids presented either adjacent or nonadjacent to each of the 20 target aircraft presented over the 40-min test phase reduced prospective memory error by 11% compared with a condition without external aids. In Experiment 2, only a single target aircraft was presented a significant time (39-42 min) after presentation of the prospective memory instruction, and the external aids reduced prospective memory error by 34%. In both experiments, costs to the efficiency of nonprospective memory air traffic management (nontarget aircraft acceptance response time, conflict detection response time) were reduced by nonadjacent aids compared with no aids or adjacent aids. In contrast, in both experiments, the efficiency of the prospective memory air traffic management (target aircraft acceptance response time) was facilitated by adjacent aids compared with nonadjacent aids. Together, these findings have potential implications for the design of automated alerting systems to maximize multitask performance in work settings where operators monitor and control demanding perceptual displays.

The Moderating Effect of Individual Differences in Error-Management Training

We investigated the effectiveness of error-encouragement training and the influence of ability and personality attribute-treatment interactions using a dynamic decision-making task. Error-encouragement training is said to be more effective than error-avoidance training because active exploration and error encouragement promote better learning and transfer. Past research, which is limited by confounded experimental designs involving simple tasks with little consideration of individual differences, provides evidence for the value of active exploration but less so for error encouragement We randomly allocated 164 participants to receive error-encouragement, error-avoidance, or no error-related instructions in training on ATC-lab, a dynamic computer simulated air traffic control task. Active exploration and task information were controlled, and ability and personality were assessed. Error encouragement yielded better transfer performance than did error avoidance but was no better than the control training. Higher- rather than lower-ability trainees benefited from training with an error orientation (positive or negative), suggesting that learning from errors in training requires greater cognitive resources. Trainees higher in openness to experience and agreeableness performed more poorly with error-avoidance training than with error-encouragement and control training. Error-avoidance training had a detrimental effect especially for those less open to experience, lower in agreeableness, and of lower ability. The significant benefits of error-encouragement training reported in previous research were probably attributable to confounding factors, such as active exploration and differential task information. Although errors and active exploration can be useful learning tools in training, trainers should be mindful that focusing on errors, whether positively or negatively, may not suit everyone.

EEG Pattern Analysis for Physiological Indicators of Mental Fatigue in Simulated Air Traffic Control Tasks

Objective: This study was designed to identify potential neurophysiologic markers and patterns of mental fatigue among air traffic controllers in their work environment.Background: The monitoring of mental fatigue in air traffic controllers has been of interest as their tasks involve high cognitive workload and are also critical to the safety of the public.Method: High-density electroencephalogram (EEG) was used to record 2-hour long air traffic control studies in eleven participants. Participants were asked to perform realistic tasks in a simulation, to operate a virtual air traffic control system. Fourier Transforms were used to estimate EEG power spectrum, statistical tests were implemented to reveal EEG spatial pattern changes caused by the time-on-task. The concept of mental state transition was introduced to study the development of certain mental states which are related to the mental fatigue. Results: The observation of EEG spectral data over a period of time revealed statistically significant changes spatially localized to central and parietal cortices. Rhythmic EEG activity within theta, alpha, and beta bands indicates transitions among mental states, which appear to be promising indicators for the development of mental fatigue. Mental fatigue indicated by the transition of mental states was estimated to approximately 70 minutes after the time on task. Application: This study can build the foundation to develop promising technologies for real time monitoring of mental fatigue, which will increase public safety and proper human resource planning.

Knowledge of Results and Signal Salience Modify Vigilance Performance and Cerebral Hemovelocity

Transcranial Doppler sonography was used to measure cerebral blood flow velocity (hemovelocity, CBFV) from the left and right middle cerebral arteries during the performance of a 30-min simulated air-traffic control task in which knowledge of results (KR) and signal salience were manipulated. Critical signals were situations in which the simulated aircraft were on a potential collision course. Findings show that overall signal detection and CBFV both declined over time. While performance was more stable over time in the KR condition, performance declined in the no-KR condition. In addition, the initial level and temporal decline in CBFV were both greater for the KR condition than the no-KR condition. Results are interpreted in terms of the motivational effects induced by feedback and a resource model of vigilance.

An Evidence Accumulation Model for Conflict Detection Performance in a Simulated Air Traffic Control Task

The aim of this article is to develop a formal model of conflict detection performance. Our model assumes that participants iteratively sample evidence regarding the state of the world and accumulate it over time. A decision is made when the evidence reaches a threshold that changes over time in response to the increasing urgency of the task. Two experiments were conducted to examine the effects of conflict geometry and timing on response proportions and response time. The model is able to predict the observed pattern of response times, including a nonmonotonic relationship between distance at point of closest approach and response time, as well as effects of angle of approach and relative velocity. The results demonstrate that evidence accumulation models provide a good account of performance on a conflict detection task. Evidence accumulation models are a form of dynamic signal detection theory, allowing for the analysis of response times as well as response proportions, and can be used for simulating human performance on dynamic decision tasks.

Experience-based mitigation of age-related performance declines: evidence from air traffic control.

Previous research has found age-related deficits in a variety of cognitive processes. However, some studies have demonstrated age-related sparing on tasks where individuals have substantial experience, often attained over many decades. Here, the authors examined whether decades of experience in a fast-paced demanding profession, air traffic control (ATC), would enable older controllers to perform at high levels of proficiency. The authors also investigated whether older controllers would show diminished age-related decrements on domain-relevant cognitive abilities. Both young and old controllers and non-controllers performed a battery of cognitive and ATC tasks. Results indicate that although high levels of experience can reduce the magnitude of age-related decline on the component processes that underlie complex task performance, this sparing is limited in scope. More important, however, the authors observed experience-based sparing on simulated ATC tasks, with the sparing being most evident on the more complex air traffic control tasks. These results suggest that given substantial experience, older adults may be quite capable of performing at high levels of proficiency on fast-paced demanding real-world tasks. The implications of these findings for global skilled labor shortages are discussed.