Human factors assessment of conflict resolution aid reliability and time pressure in future air traffic control

Though it has been reported that air traffic controllers' (ATCos') performance improves with the aid of a conflict resolution aid (CRA), the effects of imperfect automation on CRA are so far unknown. The main objective of this study was to examine the effects of imperfect automation on conflict resolution. Twelve students with ATC knowledge were instructed to complete ATC tasks in four CRA conditions including reliable, unreliable and high time pressure, unreliable and low time pressure, and manual conditions. Participants were able to resolve the designated conflicts more accurately and faster in the reliable versus unreliable CRA conditions. When comparing the unreliable CRA and manual conditions, unreliable CRA led to better conflict resolution performance and higher situation awareness. Surprisingly, high time pressure triggered better conflict resolution performance as compared to the low time pressure condition. The findings from the present study highlight the importance of CRA in future ATC operations.

Practitioner Summary: Conflict resolution aid (CRA) is a proposed automation decision aid in air traffic control (ATC). It was found in the present study that CRA was able to promote air traffic controllers' performance even when it was not perfectly reliable. These findings highlight the importance of CRA in future ATC operations.     

The role of the air traffic controller in future air traffic management: an empirical study of active control versus passive monitoring

Proposals for air traffic management such as Free Flight call for a transfer of responsibility for separation between aircraft from air traffic controllers (ATCos) to pilots. Under many proposals, the role of the ATCo will change from one of active control to passive monitoring. The present study directly compared these types of control with respect to ATCo mental workload, conflict detection, and memory. Eighteen ATCos participated in an air traffic control simulation of Free Flight procedures under moderate and high traffic load. Dependent variables included accuracy and timeliness in detecting potential conflicts, accepting and handing off aircraft, mental workload (as assessed by a secondary task, heart rate variability, and subjective ratings), and memory for aircraft location. High traffic density and passive control both degraded conflict detection performance. Actual or potential applications of this research include the recommendation that designs for future air traffic management keep authority for separation of aircraft with the controller.     

Round-trip driving effects on driving performances and mental workload under different traffic rules

This study investigates the effect of switching between different traffic rules (left-versus right-hand traffic) on driving performance and mental workload. A driving simulation environment was developed according to the real environment. Two urban roads with different traffic systems were simulated. Twenty participants executed intersection turns and continuous car-following behavior in four simulated driving stages, including driving with familiar, unfamiliar, second time unfamiliar, and back to familiar traffic rules. The mean and standard deviations for speed, distance headway, and the standard deviation of lateral position were recorded as driving performance. Mental workload was determined using the NASA-TLX and Rating Scale Mental Effort questionnaires. One-way analysis of variance was used to evaluate the differences between the four driving stages using subjective and objective measures. The results showed that significant differences were obtained in all measures when driving in the four driving situations, except for the speed standard deviation. The car-following behavior was the most unsafe (significantly larger standard deviations for distance headway and mental workload) when driving in unfamiliar road traffic compared with the other stages. When driving under unfamiliar traffic rules for the second time, the mental workload was significantly relieved and the lane-keeping ability significantly improved. The results indicated that providing an adaptive runway for drivers to familiarize themselves with different traffic rules is necessary to improve driving performance and safety. These findings provide useful information for designing bridges linking two places with different traffic rules to increase traffic safety.     

Modeling and predicting mental workload in en route air traffic control: critical review and broader implications

OBJECTIVE: We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems. BACKGROUND: Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed. METHOD: We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload. RESULTS: Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks. CONCLUSION: Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled. APPLICATION: Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems.     

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.     

Effects of different physical workload parameters on mental workload and performance

The design and evaluation of an occupational task should include an assessment of mental workload, since excessive levels of mental workload can cause errors or delayed information processing. Physically demanding work that is performed concurrently with a cognitive task may impact mental workload by impairing mental processing or decreasing performance. The primary objective of this study was to determine whether there is a differential effect of various types of physical activity on both mental workload and cognitive performance. Objective and subjective assessment tools (heart rate variability and visual analog scale) were used as indicators of mental workload, while correct responses during an arithmetic task reflected levels of performance. Thirty participants (ages 18-24 years) performed a combination of tasks inducing both physical and mental workload. Type of physical effort, frequency of movement, and force exertion level were manipulated to alter the workload associated with the physical activity. Changes in subjective ratings generally corresponded to changes in both performance on the arithmetic task and objective mental workload assessment. Some discrepancies occurred at the highest physical force exertion level as participants perceived an increase in effort to maintain the same level of performance. Further research is needed to determine the force exertion threshold, beyond which the physical effort required interferes with mental workload and/or cognitive performance.

Relevance to industry

Technological advancements have increased the requirement for many workers to execute cognitive tasks concurrently with physical activity. When designing and evaluating such situations it is important to determine the interactive effects of these activities. A simple, uni-dimensional tool is suggested as a screening tool to identify situations requiring excessive or increased mental workload that many degrade performance or place additional stress on the individual.     

Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Cognition, Technology & Work - We provide evidence for a power law relationship between the subjective one-dimensional Instantaneous Self Assessment workload measure (five-level ISA-WL scale)...     

The influence of aircraft proximity data on the subjective mental workload of controllers in the air traffic control task

This paper outlines an investigation of the impact of aircraft proximity and relationship data on the subjective mental workload of air traffic controllers. Aircraft relationships were categorized into one of 81 different categories, and these relationships were then used to predict subjective mental workload values (as reported by the participants). The results indicated that this methodology could predict subjective mental workload to an accuracy of 73%, with post-hoc analysis improving this prediction rate to 93%. These results are discussed with respect to their contribution to an understanding of the drivers of mental workload in Air Traffic Control.     

The influence of aircraft proximity data on the subjective mental workload of controllers in the air traffic control task

This paper outlines an investigation of the impact of aircraft proximity and relationship data on the subjective mental workload of air traffic controllers. Aircraft relationships were categorized into one of 81 different categories, and these relationships were then used to predict subjective mental workload values (as reported by the participants). The results indicated that this methodology could predict subjective mental workload to an accuracy of 73%, with post-hoc analysis improving this prediction rate to 93%. These results are discussed with respect to their contribution to an understanding of the drivers of mental workload in Air Traffic Control.     

Defining the drivers for accepting decision making automation in air traffic management

Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. STATEMENT OF RELEVANCE: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.     

Multimodal feedback: an assessment of performance and mental workload

Multimodal interfaces offer great potential to humanize interactions with computers by employing a multitude of perceptual channels. This paper reports on a novel multimodal interface using auditory, haptic and visual feedback in a direct manipulation task to establish new recommendations for multimodal feedback, in particular uni-, bi- and trimodal feedback. A close examination of combinations of uni-, bi- and trimodal feedback is necessary to determine which enhances performance without increasing workload. Thirty-two participants were asked to complete a task consisting of a series of 'drag-and-drops' while the type of feedback was manipulated. Each participant was exposed to three unimodal feedback conditions, three bimodal feedback conditions and one trimodal feedback condition that used auditory, visual and haptic feedback alone, and in combination. Performance under the different conditions was assessed with measures of trial completion time, target highlight time and a self-reported workload assessment captured by the NASA Task Load Index (NASA-TLX). The findings suggest that certain types of bimodal feedback can enhance performance while lowering self-perceived mental demand.     

Multimodal feedback: an assessment of performance and mental workload

Multimodal interfaces offer great potential to humanize interactions with computers by employing a multitude of perceptual channels. This paper reports on a novel multimodal interface using auditory, haptic and visual feedback in a direct manipulation task to establish new recommendations for multimodal feedback, in particular uni-, bi- and trimodal feedback. A close examination of combinations of uni-, bi- and trimodal feedback is necessary to determine which enhances performance without increasing workload. Thirty-two participants were asked to complete a task consisting of a series of ‘drag-and-drops’ while the type of feedback was manipulated. Each participant was exposed to three unimodal feedback conditions, three bimodal feedback conditions and one trimodal feedback condition that used auditory, visual and haptic feedback alone, and in combination. Performance under the different conditions was assessed with measures of trial completion time, target highlight time and a self-reported workload assessment captured by the NASA Task Load Index (NASA-TLX). The findings suggest that certain types of bimodal feedback can enhance performance while lowering self-perceived mental demand.     

Dynamic problem selection in air traffic control training: a comparison between performance,mental effort and mental efficiency

The differential effects on training and training outcome of four methods of problem selection were investigated in a computer-based training for air traffic control. In one method, training problems were given to the participants in a fixed predetermined sequence, from simple to complex. In the other methods, problems were selected dynamically, based on three different learner variables. These were mental effort, performance and mental efficiency, which is a variable that combines mental effort and performance measures to determine problem efficiency. After the training, transfer was measured. The hypothesis that dynamic problem selection would lead to more efficient training than non-dynamic problem selection was confirmed. The second hypothesis, that dynamic problem selection based on mental efficiency would lead to more efficient training and better transfer than dynamic problem selection based on performance or mental effort alone was not supported. However, the efficiency measures of the three variables were distorted by the differential effects of these variables on the acquisition phase. A possible explanation for the results is that selection based on performance stimulates rule automation, whereas selection based on mental effort or mental efficiency leads to schema acquisition.     

Human performance assessment of a single air traffic controller conducting multiple remote tower operations

The innovative concept of multiple remote tower operations (MRTO) can maximize cost savings by applying video panorama‐based remote tower working positions, which can facilitate fewer air traffic controllers (ATCO) to provide the air traffic services (ATS) function for more airports. Five subject‐matter experts, qualified remote tower ATCOs, participated in this research work by applying the human error template (HET) and comparing workload between physical tower operations and MRTO using NASA‐TLX (Task Load Index). The results demonstrate that augmented visualization provided sufficient technical support for a single ATCO to perform tasks originally designed to be performed by four ATCOs, however, the demands of the associated multiple tasks induced significant workload. There were significant differences in ATCOs’ mental demand, temporal demand, effort, and frustration between MRTO and physical tower operations. This innovative technology may induce human–computer interaction (HCI) issues that impact ATCO's perceived workload. This creates a need for further research on how to manage ATCO's workload in a multiple remote tower environment. This research work provided scientific evidence that MRTO can achieve the objectives of Single European Sky Air Traffic Management Research program. The findings can be applied to both ATCO training design and remote tower system design.     

Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

The management of uncertainty is a critical aspect of current as well as future air traffic control operations. This study investigated: (1) sources of uncertainty in enroute air traffic control, (2) strategies that air traffic controllers adopt to cope with uncertainty, (3) the trade-offs and contingencies that influences the adoption of these uncertainties, and (4) the requirements for system design that support controllers in following these strategies. The data were collected using a field study in two enroute air traffic control centres, involving “over the shoulder” observation sessions, discussions with air traffic controllers, and document analysis. Three types of uncertainty coping strategies were identified: reducing uncertainty, acknowledging uncertainty, and increasing uncertainty. The RAWFS heuristic (Lipshitz and Strauss in Organ Behav Hum Decis Process 69:149–163, 1997) and anticipatory thinking (Klein et al. in Anticipatory thinking, Proceedings of the eighth international NDM conference, Pacific Grove, CA, 2007) were used to identify reduction and acknowledgement strategies. Recent suggestions by Grote (Saf Sci 71:71–79, 2015) were used to further explore strategies that increase uncertainty. The study presents a new framework for the classification of uncertainties in enroute air traffic control and identified the uncertainty management strategies and underlying tactics, in context of contingencies and trade-offs between operational goals. The results showed that controllers, in addition to reducing and acknowledging uncertainty, may deliberately increase uncertainty in order to increase flexibility for other actors in the system to meet their operational goals. The study describes new tactics for acknowledging and increasing uncertainty. The findings were summarized in the air traffic controller complexity and uncertainty management model. Additionally, the results bring to light system design recommendations that allow controllers to follow these different coping strategies, including (1) the design of alerts, (2) the transparency of prediction tools, and (3) system flexibility as a requirement for acknowledging and increasing uncertainty. The results are particularly important as uncertainty is likely to increase in future operations of enroute air traffic control, requiring automation support for controllers. Implications for future air traffic management scenarios as envisioned within the SESAR Joint Undertaking (SESAR JU in European ATM Master Plan, 2 eds, 2012) and NextGen (FAA in FAA’s NextGen implementation plan, 2014) operational concepts are discussed.     

Human–automation teams and adaptable control for future air traffic management

The design and management of human–automation teams for future air traffic systems require an understanding of principles of cognitive systems engineering, allocation of function and team adaptation. The current article proposes a framework of human–automation team adaptable control that incorporates adaptable automation [Oppermann, R., Simm, H., 1994. Adaptability: user-initiated individualization. In: Oppermann, R. (Ed.), Adaptive User Support: Ergonomic Design of Manually and Automatically Adaptable Software. Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 14–64] with an Extended Control Model of Joint Cognitive System functioning [Hollnagel, E., Nåbo, A., Lau, I., 21–24 July 2003. A systemic model for driver-in-control. In: Paper Presented at the Second International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, Public Policy Center, University of Iowa, Park City, UT] nested within a dynamic view of team adaptation [Burke, C.S., Stagl, K.C., Salas, E., Pierce, L., Kendall, D., 2006. Understanding team adaptation: a conceptual analysis and model. Journal of Applied Psychology 91, 1189–1207]. Modeling the temporal dynamics of the coordination of human–automation teams under conditions of Free Flight requires an appreciation of the episodic, cyclical nature of team processes from transition to action phases, along with the distinction of team processes from emergent states [Marks, M.A., Mathieu, J.E., Zaccaro, S.J., 2001. A temporally based framework and taxonomy of team processes. Academy of Management Review 26, 356–376]. The conceptual framework of human–automation team adaptable control provides a basis for future research and design.

Relevance to industry

The current article provides a conceptual framework to direct future investigations to determine the optimal design and management of Human–automation teams for Free Flight-based air traffic management systems.     

Effects of light and heavy workload on air traffic tactical operations: a hazard rate model

This paper introduces a class of event history analysis used to examine how the operations of an air traffic controller change under light and heavy traffic workload. The analysis begins by assessing the hazard rate, h(t), of a transition (or spell) between the controller's communication and flight progress activities. h(t) is the instantaneous rate of going from one state (i.e. an activity of communication or flight progress) to another in a unit of time, given that the controller has been in the first state until time t. Results indicated that the spell distribution closely followed a Weibull distribution, a prerequisite for this analysis. The results also indicated that h(t) was more likely regulated by time in heavy than in light workload conditions, and that under heavy workload, indirect speech from the planner controller would decrease the h(t) for communication to flight progress spells. The results suggest that a dynamic model for the analysis of air traffic control may be necessary, and that the implications of using modular automation may not be straightforward. This technique may be of general use to examine temporal regularities in operating real-time control tasks.     

From trees to forest: relational complexity network and workload of air traffic controllers

In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed.     

Analysis of the mental workload of city traffic control operators while monitoring traffic density: A field study

IntroductionIt is important to evaluate when and why the mental workload of operators increases during system operation. The city traffic control center (TCC) is a complex work system, and it is important to describe MW as a condition related to this. The purpose of this study is to evaluate the mental workload of operators while monitoring traffic loads in the city TCC.MethodsElectroencephalography and electrooculography data were collected from 16 operators while performing their daily work, in four conditions: resting state, low traffic density, high traffic density, and recovery. The Simplified-Subjective Workload Assessment Technique (S-SWAT) was used to evaluate the subjective workload of operators.ResultsThe findings indicate that operators experience a larger mental workload during high traffic density than during low traffic density (p < 0.001). TCC stressors led to significant changes in EEG bands, such as theta, alpha, and eye activity. Significant differences were observed for subjective ratings of MW (p < 0.001).ConclusionAlthough the working situations of TCC operators are repeated daily, their mental fatigue and stress level gradually increase, leading to deterioration in their mental health. It may be necessary periodically to monitor their mental health and to consider their organizational behavior during traffic density monitoring.Relevance to industrycomplex work systems have increased the requirement for many operators to conduct mental tasks in real work conditions such as city traffic density monitoring. When evaluating such workplaces, it is important to identify situations requiring increased mental workload that might impose additional stress on operators, decreasing their performance. Based on the results, the traffic control center director would be aware of the MW condition of the operators.