Simulated Air Traffic Control Research Articles

The influence of task load on situation awareness and control strategy in the ATC tower environment

The safe and efficient operation of air traffic is highly dependent on the performance of the Air Traffic Control Officer (ATCO). The ATCOs control the traffic within defined areas by monitoring the traffic and granting clearances. A key element in analyzing the ATCOs is their interaction with the environment through their workplace. Especially the influence of task load on their situation awareness (SA) and applied control strategy provides information on the quality of the workplace. As task load increases, controllers are able to maintain performance by using different management or compensation strategies. This article supports the evaluation of ATCO’s workplaces by focusing on whether probe techniques for assessing SA are applicable for tower control operation and for measuring the influences of increased task load on the control strategy. An experiment with nine ATCOs was conducted in a simulated real-time air traffic control environment. Different measurements for SA were applied and compared regarding their efficiency and validity. The manipulation of task load and visibility influenced the SA and control strategy at the same time. Performance metrics were selected in advance to evaluate the participant’s efficiency. SA was measured with a probe technique and an offline self-assessment method. Findings suggest that probe techniques increase the insight into the understanding of SA in comparison to self-assessment and that they are applicable to the air traffic control environment. Control strategies were derived from the information-gathering process via the eye-movement behavior and connected to task load. The results imply that SA is part of the individual performance and that increasing demand through task load is handled with an adaptation of the control strategy.

Multifactor interactions and the air traffic controller: the interaction of situation awareness and workload in association with automation

Air traffic controllers must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur and interact to affect performance. However, multifactor influences and the association with performance are under-researched. This study utilised a high-fidelity, human-in-the-loop, en route air traffic control simulation to investigate the relationship between workload, situation awareness and controller performance. The current study aimed to replicate Edwards et al.’s (in: Proceedings of the 4th AHFE international conference, 21–25th July, San Francisco, USA, 2012) previous finding that factors known to be associated with controller performance do co-vary and can interact, which is associated with a compound influence on performance. In addition, the current study aimed to extend Edwards et al.’s (2012) study by engaging retired controllers as participants and comparing multifactor relationships across four levels of automation. Results suggest that workload and situation awareness may interact to produce a compound (as opposed to cumulative) impact on controller performance. In addition, the effect of the interaction on performance may be dependent on the context and level of automation. Findings have implications for human–automation teaming in air traffic control, and the potential prediction of performance-influencing situations, supporting controller performance in the operational environment.

The Relationship between Workload and Performance in Air Traffic Control

In air traffic control, task demand and workload have important implications for the safety and efficiency of air traffic. Task demand is dynamic, however, research on demand transitions and associated controller perception and performance is limited. In addition, there is a comparatively restricted understanding of the influence of task demand transitions on workload and performance, in association with automation. This study used an air traffic control simulation to investigate the influence of task demand transitions and two conditions of varying automation, on workload and efficiency-related performance. Findings showed that both the direction of the task demand variation, and the amount of automation, influenced the relationship between workload and performance. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

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

Метод оптимального розв’язання групових конфліктних ситуацій між повітряними суднами у тривимірному просторі

Мета: В сучасних умовах високої динамічності і щільності повітряного руху значно зростає небезпека критичного зближення відразу декількох повітряних суден і виникнення групових конфліктних ситуацій. Актуальною проблемою є розробка методів оптимального розв’язання групових конфліктних ситуацій, які повинні забезпечувати синтез безконфліктних траєкторій у тривимірному просторі. Методи: Розроблено метод оптимального розв’язання групових конфліктних ситуацій із застосуванням маневрування зміною курсу, швидкості та висоти польоту. Критеріями оптимальності визначені регулярність, економічність польотів і складність маневрування. Метод полягає у послідовному синтезі множини Парето-оптимальних комбінацій безконфліктних траєкторій сукупності повітряних суден з використанням дискретного багатокритеріального динамічного програмування та визначенні оптимальної комбінації із застосуванням із застосуванням згортки критеріїв оптимальності. В рамках методу визначено: процедуру формування безконфліктних комбінацій станів сукупності повітряних суден, які визначають комбінації Парето-оптимальних траєкторій; обмеження, які накладаються при дискретизації процесу розв’язання конфлікту для забезпечення відсутності неспостережуваних порушень ешелонування. Результати: Дослідження запропонованого методу виконано шляхом комп’ютерного моделювання, результати якого показали, що синтезована комбінація безконфліктних траєкторія забезпечує усунення групової конфліктної ситуації та відповідає встановленим критеріям оптимальності. Обговорення: Запропонований метод може бути використаний при розробці нових автоматизованих систем управління повітряним рухом, бортових систем попередження зіткнень, інтелектуальних тренажерів керування повітряним рухом та для проведення наукових досліджень.

Simulation Challenges – Student Perception of Air Traffic Control Simulation

Simulation Challenges – Student Perception of Air Traffic Control Simulation

FOSS BASED AIR TRAFFIC CONTROL SIMULATOR

This paper presents an analysis of the significance of Air Traffic Control (ATC) simulators in training, and focuses on the development of low cost, high awareness ATC simulator on a 3D virtual environment, using Free and Open Source Aircraft simulator named Flightgear. Here it has proposed a scenario based ATC officer control method covering the all three phases; tower control, approach and enroute control.

항공교통관제 시뮬레이션을 위한 개선된 5 자유도 항공기 운동 모델 개발 및 검증방안 연구

항공교통관제 시뮬레이션을 위한 개선된 5 자유도 항공기 운동 모델 개발 및 검증방안 연구

On the Nature of Interruptions in Complex Dynamic Tasks

The formal study of interruption can improve workplace safety by providing insights into the cognitive processes underlying interrupted task performance (Boehm-Davis & Remington, 2009). Experimental studies examining the disruptive effects of interruptions have typically used basic laboratory paradigms (Trafton & Monk, 2007) and account for disruptive effects using prospective memory models (McDaniel, Einstein, Graham, & Rall, 2004) or activation-based models (Altmann & Trafton, 2002). However, the effects of interruptions in more complex dynamic tasks, such as air traffic control (ATC), may be different because they require operators to perform multiple task goals in a continuously evolving task environment. The current study examined the impact of two kinds of interruption on performance in simulated ATC. Participants ( n = 60) were required to accept/handoff aircraft entering/exiting their sector and to prevent aircraft pairs from conflicting (violating minimum separation standards). There were three within-subjects conditions: no-interruption (baseline control), a blank interruption (blank screen for 27s), and an n-back interruption (visual 2-back task, for 27s). Each ATC trial included two delayed-execute PM tasks: a conflict-resolution PM-task and a handoff PM-task. Both tasks were encoded before the interruption occurred. The conflict-resolution PM-task required participants to resolve a deferred conflict immediately after the interruption ended. Time taken to resolve this conflict was taken as resumption time. We predicted resumption time would increase for both interruption conditions due to the need to reorientate to the evolved visual ATC scene. We also predicted the n-back interruption would further increase resumption time due to blocking rehearsal. Interruptions significantly increased resumption time. However, in contrast to previous research using basic tasks (Monk, Trafton, & Boehm-Davis, 2008) resumption time was not greater in the demanding n-back interruption relative to the blank interruption. The handoff PM-task required participants to handoff an aircraft using a non-routine keystroke at 63s (on average) after the interruption. To be clear, the aircraft flashed for hand-off and the participant needed to remember to press the alternative handoff key instead of the routine handoff key. Prior research has examined PM in simulated ATC (Loft, 2014), and we extended it by examining how interruptions would impact PM. Based on findings in basic delayed-execute studies, we predicted interruptions would increase handoff PM-task errors. The average error rate on the handoff PM-task was 31%, but this did not differ between the conditions. Two important findings emerged from this study. Firstly, we did not find rehearsal to be an important factor in interruption recovery in simulated ATC. This indicates that orientating to an evolved visual scene may be the primary driver behind resumption time costs in this dynamic task. Secondly, we replicated the PM errors reported in previous simulated ATC experiments, but found that PM performance was robust to interruptions. Whilst the use of a student sample with limited training limits the generalizability of the present study, we recommend psychological models of interruption be applied cautiously, particularly in safety-critical environments. Human factors practice and research will benefit from further examining the nature of interruptions in complex task environments.

Reducing prospective memory error and costs in simulated air traffic control: External aids, extending practice, and removing perceived memory requirements.

In air traffic control (ATC), forgetting to perform deferred actions-prospective memory (PM) errors-can have severe consequences. PM demands can also interfere with ongoing tasks (costs). We examined the extent to which PM errors and costs were reduced in simulated ATC by providing extended practice, or by providing external aids combined with extended practice, or by providing external aids combined with instructions that removed perceived memory requirements. Participants accepted/handed-off aircraft and detected conflicts. For the PM task, participants were required to substitute alternative actions for routine actions when accepting aircraft. In Experiment 1, when no aids were provided, PM errors and costs were not reduced by practice. When aids were provided, costs observed early in practice were eliminated with practice, but residual PM errors remained. Experiment 2 provided more limited practice with aids, but instructions that did not frame the PM task as a "memory" task led to high PM accuracy without costs. Attention-allocation policies that participants set based on expected PM demands were modified as individuals were increasingly exposed to reliable aids, or were given instructions that removed perceived memory requirements. These findings have implications for the design of aids for individuals who monitor multi-item dynamic displays. (PsycINFO Database Record

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.

Workload, Risks, and Goal Framing as Antecedents of Shortcut Behaviors

Shortcut behaviors are methods of completing a task that require less time than typical or standard procedures. These behaviors carry the benefit of increasing efficiency, yet can also carry risks (e.g., of an accident). The purpose of this research is to understand the reasons individuals engage in shortcut behaviors, even when doing so is known to be risky. We present two laboratory studies (N = 121 and N = 144) in which participants performed an air traffic control simulation. Participants could improve efficiency by taking shortcuts; that is, by sending aircraft off the prescribed flight paths. This design allowed for direct and unobtrusive observation of shortcut behaviors. Individuals who were told that efficiency was an obligation tended to believe that shortcut behaviors had utility for managing high workloads, even when the risks associated with shortcuts were high. Downstream, utility perceptions were positively related to actual shortcut behavior. Although communicating risks may be used to help individuals balance the “pros” and “cons” of shortcut behaviors, goal framing is also important. Subtle cues indicating that efficiency is an obligation can lead to elevated perceptions of the utility of shortcut behaviors, even when knowing that engaging in shortcut behaviors is very risky. Past research has provided limited insights into the reasons individuals sometimes engage in shortcut behaviors even when doing so is known to be risky. The current research speaks to this issue by identifying workload and obligation framing as antecedents of the decision to take shortcuts.

Air traffic control: Ocular metrics reflect cognitive complexity

The objective of the study was to evaluate effects of complexity on cognitive workload in a simulated air traffic control conflict detection task by means of eye movements recording. We manipulated two complexity factors, convergence angle and aircrafts minimum distance at closest approach, in a multidimensional workload assessment method based on psychophysiological, performance, and subjective measures. Conflict trials resulted more complex and time-consuming than no conflicts, requiring more frequent fixations and saccades. Moreover, large saccades showed reduced burst power with higher task complexity. A motion-based and a ratio-based strategy were suggested for conflicts and no conflicts on the basis of ocular metrics analysis: aircrafts differential speed and distance to convergence point at trial start were considered determinant for strategy adoption. Relevance to industryEye metrics measurement for online workload assessment enhances better identification of workload-inducing scenarios and adopted strategy for traffic management. System design, as well as air traffic control operators training programs, might benefit from on line workload measurement.

Context-sensitive reward shaping for sparse interaction multi-agent systems

AbstractPotential-based reward shaping is a commonly used approach in reinforcement learning to direct exploration based on prior knowledge. Both in single and multi-agent settings this technique speeds up learning without losing any theoretical convergence guarantees. However, if speed ups through reward shaping are to be achieved in multi-agent environments, a different shaping signal should be used for each context in which agents have a different subgoal or when agents are involved in a different interaction situation.This paper describes the use of context-aware potential functions in a multi-agent system in which the interactions between agents are sparse. This means that, unknown to the agentsa priori, the interactions between the agents only occur sporadically in certain regions of the state space. During these interactions, agents need to coordinate in order to reach the global optimal solution.We demonstrate how different reward shaping functions can be used on top of Future Coordinating Q-learning (FCQ-learning); an algorithm capable of automatically detecting when agents should take each other into consideration. Using FCQ-learning, coordination problems can even be anticipated before the actual problems occur, allowing the problems to be solved timely. We evaluate our approach on a range of gridworld problems, as well as a simulation of air traffic control.

Impact of Automation Support on the Conflict Resolution Task in a Human-in-the-Loop Air Traffic Control Simulation

Abstract: To determine the capabilities and limitations of human operators and automation in separation assurance roles, the second of three Human-in-the-Loop (HITL) part-task studies investigated air traffic controllers’ ability to detect and resolve conflicts under varying task sets, traffic densities, and run lengths. Operations remained within a single sector, staffed by a single controller, and explored, among other things, the controller’s responsibility for conflict resolution with or without their involvement in the conflict detection task. Furthermore, these conditions were examined across two different traffic densities; 1x (current-day traffic) and a 20% increase above current-day traffic levels (1.2x). Analyses herein offer an examination of the conflict resolution strategies employed by controllers. In particular, data in the form of elapsed time between conflict detection and conflict resolution are used to assess if, and how, the controllers’ involvement in the conflict detection task affected the way in which they resolved traffic conflicts.

Using memory for prior aircraft events to detect conflicts under conditions of proactive air traffic control and with concurrent task requirements.

In 2 experiments we examined the impact of memory for prior events on conflict detection in simulated air traffic control under conditions where individuals proactively controlled aircraft and completed concurrent tasks. Individuals were faster to detect conflicts that had repeatedly been presented during training (positive transfer). Bayesian statistics indicated strong evidence for the null hypothesis that conflict detection was not impaired for events that resembled an aircraft pair that had repeatedly come close to conflicting during training. This is likely because aircraft altitude (the feature manipulated between training and test) was attended to by participants when proactively controlling aircraft. In contrast, a minor change to the relative position of a repeated nonconflicting aircraft pair moderately impaired conflict detection (negative transfer). There was strong evidence for the null hypothesis that positive transfer was not impacted by dividing participant attention, which suggests that part of the information retrieved regarding prior aircraft events was perceptual (the new aircraft pair "looked" like a conflict based on familiarity). These findings extend the effects previously reported by Loft, Humphreys, and Neal (2004), answering the recent strong and unanimous calls across the psychological science discipline to formally establish the robustness and generality of previously published effects. (PsycINFO Database Record

Multifactor interactions and the air traffic controller: The interaction of situation awareness and workload in association with automation

Abstract: Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur and interact to affect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop en-route air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The current study aimed to replicate Edwards, Sharples, Wilson and Kirwan’s (2012) previous research, and extend the study by using a ex-controllers as participants, and comparing multifactor relationships across four levels of automation. Results suggest that workload and situation awareness may interact to produce a compound impact on controller performance. In addition, the effect of the interaction on performance may be dependent on the context and level of automation. Findings have implications for human-automation teaming in air traffic control, and the potential prediction, and therefore support, of ATCO performance.

Petri-Net-Based Modeling of Human Operator's Planning for the Evaluation of Task Performance Using the Example of Air Traffic Control

With respect to planning capabilities, a model is developed to be used for the evaluation of human operator's cognitive performance. Plans are goal-directed interaction sequences cognitively simulated before appearing in dynamic human–machine systems. In this context, human operator's actions have long-term effects as well as different consequences depending on the time of their activation. The proposed model allows the evaluation of cognitive task performance by comparing implemented decisions to the available options represented by plans. In this paper, situation operator modeling is applied to describe operator's behavior and the planning process based on the system modeled using colored Petri Nets. The Petri Net is applied for the prediction of future system states. The planning model uses a set of rules that describe the normative behavior of operators as definitions of problems and actions required to avoid these. The rules are derived systematically from the operator's objectives and from the available actions. The proposed method allows the calculation and, therefore, the prediction of future states as well as possible upcoming conflicts within the system. Corresponding rules may modify and, therefore, affect the generated plan. The method is demonstrated using a simplified air traffic control simulation. This method extends earlier methods published by the authors for the determination of available options based on Petri Nets. It can be concluded that the calculation of sequences of actions for interaction with dynamic systems with constant change over time is possible and realized for the first time.

NextSim

The Federal Aviation Administration expects a large increase in air traffic over the next 15 to 20 years. In response, the Next Generation Air Transportation System (NextGen) has been proposed, which will use newer technologies and automation to shift the way air traffic is managed. Many of the proposed changes need to be tested before implantation begins, but it is difficult to conduct human factors tests on an environment that does not yet exist. We describe an air traffic control (ATC) simulator developed for this purpose. NextSim is an ATC research simulator that collects performance, workload, and situation awareness data to address human factors/ergonomics issues that might arise in NextGen.