Managing emergencies and abnormal situations in air traffic control (part I): Taskwork strategies

A lot of research in Air Traffic Control (ATC) has focused on human errors in decision making whilst little attention has been paid to the cognitive strategies employed by controllers in managing abnormal situations. This study looks into cognitive strategies in taskwork that enable controllers to become resilient decision-makers. Two field studies were carried out where novice and experienced controllers were observed in simulator training in emergency and unusual scenarios. A prototype model of taskwork strategies in air traffic management was developed and its construct validity was tested in the context of the field studies. A companion study (part II), follows that investigates aspects of teamwork in the same field and contributes to the development of a generic model of Taskwork & Teamwork strategies in Emergencies in Air traffic Management (T²EAM). The final section addresses the difficulties experienced by novice controllers and explains taskwork strategies employed by experts to manage uncertainty and balance workload in simulator emergencies.     

Implementing agent teams in dynamic multiagent environments

Teamwork is becoming increasingly critical in multiagent environments ranging from virtual environments for training and education, to information integration on the internet, to potential multirobotic space missions. Teamwork in such complex, dynamic environments is more than a simple union of simultaneous individual activity, even if supplemented with preplanned coordination. Indeed, in these dynamic environments, unanticipated events can easily cause a breakdown in such preplanned coordination. The central hypothesis in this article is that for effective teamwork, agents should be provided explicit representation of team goals and plans, as well as an explicit representation of a model of teamwork to support the execution of team plans. In our work, this model of teamwork takes the form of a set of domain independent rules that clearly outline an agent's commitments and responsibilities as a participant in team activities, and thus guide the agent's social activities while executing team plans. This article describes two implementations of agent-teams based on the above principles, one for a realworld helicopter combat simulation, and one for the RoboCup soccer simulation. The article also provides a preliminary comparison of the two agent-teams to illustrate some of the strengths and weaknesses of RoboCup as a common test bed for multiagent systems.     

From roles to teamwork: A framework and architecture

Teamwork requires organization, strategies, and coordination. The design of a multiagent system should support these conceptual properties for constructing effective teams. The advantage of a teamwork approach is the reduction in complexity of the task through distribution of responsibilities, resulting in better utilization of resources, robust behaviors, and a greater variety of behaviors against competitors. In this article a framework for building teams of responsible agents using roles, responsibilities, and strategies is described. Its application to the domain of soccer is used to design a high-performance team of soccer agents. The architecture for these agents utilizes a reactive planning system with support for teamwork. The team of soccer agents will be tested in a series of competitions against other teams in the real-time soccer simulator proposed for Robocup-97, which provides an uncertain, resource bounded world.     

Studying distributed cognition of simulation-based team training with DiCoT

Health care organizations employ simulation-based team training (SBTT) to improve skill, communication and coordination in a broad range of critical care contexts. Quantitative approaches, such as team performance measurements, are predominantly used to measure SBTTs effectiveness. However, a practical evaluation method that examines how this approach supports cognition and teamwork is missing. We have applied Distributed Cognition for Teamwork (DiCoT), a method for analysing cognition and collaboration aspects of work settings, with the purpose of assessing the methodology’s usefulness for evaluating SBTTs. In a case study, we observed and analysed four Emergo Train System® simulation exercises where medical professionals trained emergency response routines. The study suggests that DiCoT is an applicable and learnable tool for determining key distributed cognition attributes of SBTTs that are of importance for the simulation validity of training environments. Moreover, we discuss and exemplify how DiCoT supports design of SBTTs with a focus on transfer and validity characteristics.

Practitioner Summary: In this study, we have evaluated a method to assess simulation-based team training environments from a cognitive ergonomics perspective. Using a case study, we analysed Distributed Cognition for Teamwork (DiCoT) by applying it to the Emergo Train System®. We conclude that DiCoT is useful for SBTT evaluation and simulator (re)design.     

Effects of metacognition in cooperation on team behaviors

Traditional studies on measurements and training of teamwork have often focused on observational teamwork behaviors; however, measurements and training of unobservable teamwork such as mutual performance monitoring are also important for improving teamwork measurement and training. In addition, an improvement of cognitive mechanisms underlying teamwork must effectively be able to enhance team performance because sufficient situation awareness of status of team is expected to be a requirement for positive teamwork behaviors. This study focuses on metacognition in cooperation that underlies team cooperation and aims to investigate the importance of metacognition in cooperation by analyzing contents of reflection on cooperation collected in our previous study in terms of our proposed model about metacognition in cooperation. The comparisons of metacognition in cooperation elicited in a team experiment and team performance indexes suggest that an expansion of range of metacognition in cooperation by metacognitive instructions will enhance team performance and that certain types of metacognition in cooperation are important for positive teamwork.     

Automatic generation of communication and teamwork within multi-agent teams

Teamwork and communication are two important processes within multi-agent systems designed to act in a coherent and coordinated manner. Modeling teamwork involves interleaving steps within shared plans that will allow agents to work together towards common goals. These steps involve reasoning about roles, responsibilities, and joint-intentions in order to coordinate activity amongst individuals. Communication facilitates teamwork. There are various complex forms of communication such as synchronization, coordination, and cooperation that allow for members of teams to use teamwork to their advantage. Explicitly defining every possible communication point within a team plan is too cumbersome and inflexible. In this paper, we describe a method to automatically decompose a team plan into a collection of individual agent plans, inserting all of the necessary communication points needed to properly generate coordinated behavior. This approach could be used to more accurately and easily model teamwork in multi-agent systems.     

An exploratory study: a measure of workload associated with teamwork

Team workload, which is usually described as an index of the ratio of available team resources to task demands, is believed to be critical for optimal human–computer integration. Although research conceptualizing team workload suggests that the measurement of team workload should consider workload unique to the team, the sum/min/max of members’ workload associated with taskwork referring to individual task performance is often used as an indicator of team workload. In order to better assess workload in team performance in which more than two individuals cooperate and conduct a task, it is also necessary to assess members’ workload associated with teamwork that refers to interpersonal interactions among individuals. The present study aims to develop a measure of workload associated with teamwork and discuss its contribution to operationalizing team workload. Results of team experiments indicate that the Teamwork Workload Scale is able to assess workload associated with teamwork and that it is necessary to assess both workload associated with taskwork and teamwork in order to better assess workload in team performance and operationalize team workload. In order to operationalize and measure team workload, it is necessary to investigate workload in team performance using quantitative data.     

On teams, teamwork, and team performance: discoveries and developments

OBJECTIVE: We highlight some of the key discoveries and developments in the area of team performance over the past 50 years, especially as reflected in the pages of Human Factors. BACKGROUND: Teams increasingly have become a way of life in many organizations, and research has kept up with the pace. METHOD: We have characterized progress in the field in terms of eight discoveries and five challenges. RESULTS: Discoveries pertain to the importance of shared cognition, the measurement of shared cognition, advances in team training, the use of synthetic task environments for research, factors influencing team effectiveness, models of team effectiveness, a multidisciplinary perspective, and training and technological interventions designed to improve team effectiveness. Challenges that are faced in the coming decades include an increased emphasis on team cognition; reconfigurable, adaptive teams; multicultural influences; and the need for naturalistic study and better measurement. CONCLUSION: Work in human factors has contributed significantly to the science and practice of teams, teamwork, and team performance. Future work must keep pace with the increasing use of teams in organizations. APPLICATION: The science of teams contributes to team effectiveness in the same way that the science of individual performance contributes to individual effectiveness.     

Analyses of team performance in a dynamic task environment

Teamwork, a central component of team research, is not readily observable and must be inferred from the manner in which teams operate. Of particular interest is the measurement and evaluation of teamwork. The goal of this paper is to explore the assessment of team data using a temporal accuracy measure called the Relative Accuracy Index (RAI). For the statistical analysis, the generalized mixed model was applied. This model is applicable for binomial data and takes into account the correlation structure within team members. We describe the statistical procedure in detail, aiming to guide researchers who encounter similar problems. Using our statistical analysis, we found that participants whose training focused on coordination activities outperformed those whose training did not. Moreover, we found that workload stress accentuates the difference.     

Exploring similarities and differences in teamwork across diverse healthcare contexts using communication analysis

Teamwork is prevalent in many work contexts. This study explored the similarities and differences in teamwork processes across different healthcare work contexts with the aim of assessing knowledge transfer feasibility. The research approach was to aggregate team communication analyses from four healthcare contexts to uncover teamwork similarities and differences. The four healthcare contexts included two handoffs and two surgery contexts. The communication analysis segmented communication into meaningful sequences. It categorized utterances into content categories and verbal behaviors. There were a few similar content categories across the four contexts. A clear information structure emerged in the two handoff contexts. In addition, there were more dialogues and requests in the surgeries compared to more reports in the handoffs. The content similarities suggest that some knowledge is transferable among the contexts. However, the differences in communication patterns reflect fundamental differences between handoff and surgery contexts in some teamwork processes. This research demonstrated that using communication analysis can uncover similarities and differences in team cognition and teamwork processes across work contexts. This in turn can help determine what knowledge and methods pertaining to team training, procedures, and technology are transferable across the contexts.     

Team members' perceptions of online teamwork learning experiences and building teamwork trust: A qualitative study

Teamwork factors can facilitate team members, committing themselves to the purposes of maximizing their own and others' contributions and successes. It is important for online instructors to comprehend students' expectations on learning collaboratively. The aims of this study were to investigate online collaborative learning experiences and to identify important factors that were crucial for building teamwork trust. A qualitative research method was utilized in the study. Data were collected from students' responses of three open-ended questions and interviews. The results indicated that students who enjoyed working in the group setting had a good relationship with their team members and they trusted their team members. In contrast, the questionable behaviors of members (lack of communication and low level of individual accountability) were negative factors of their teamwork experiences. In addition, students considered individual accountability, familiarity with team members, commitment toward quality work, and team cohesion were important factors for building trust with team members. Quantitative analyses confirmed that teamwork trust was correlated significantly with two of the important factors for building trust indicated by team members: familiarity with members (r = .74) and team cohesion (r = .79). Implications and recommendations for future research were also discussed.     

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.     

Facilitating Collocated Crowdsourcing on Situated Displays

Online crowdsourcing enables the distribution of work to a global labor force as small and often repetitive tasks. Recently, situated crowdsourcing has emerged as a complementary enabler to elicit labor in specific locations and from specific crowds. Teamwork in online crowdsourcing has been recently shown to increase the quality of output, but teamwork in situated crowdsourcing remains unexplored. We set out to fill this gap. We present a generic crowdsourcing platform that supports situated teamwork and provide experiences from a laboratory study that focused on comparing traditional online crowdsourcing to situated team-based crowdsourcing. We built a crowdsourcing desk that hosts three networked terminal displays. The displays run our custom team-driven crowdsourcing platform that was used to investigate collocated crowdsourcing in small teams. In addition to analyzing quantitative data, we provide findings based on questionnaires, interviews, and observations. We highlight 1) emerging differences between traditional and collocated crowdsourcing, 2) the collaboration strategies that teams exhibited in collocated crowdsourcing, and 3) that a priori team familiarity does not significantly affect collocated interaction in crowdsourcing. The approach we introduce is a novel multi-display crowdsourcing setup that supports collocated labor teams and along with the reported study makes specific contributions to situated crowdsourcing research.     

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.     

Analysis of the performance characteristics of controllers’ strategies in en route air traffic control tasks

For addressing human factor issues in the air traffic control (ATC) domain, further comprehension of controllers’ working methods during actual work is required. The objective of the present research is to analyze the performance characteristics of control strategies, which can be a major means to manage a traffic situation and workload for controllers, by using our process visualization tool of ATC tasks called COMPASi (COMPAS in interactive mode/COMPAS: COgnitive system Model for simulating Projection-based behaviors of Air traffic controllers in dynamic Situations). The computer-based simulation using COMPASi has clearly demonstrated the performance differences in the types of control strategies derived from a high-fidelity human-in-the-loop simulation (HITLS) for safety, efficiency of completing ATC tasks, and fuel economy of aircraft in a specific situation, and also differences in their tolerance of situational variability. The analysis results have been supported by performance evaluations carried out by ATC training instructors. In addition, a comparative analysis between simulation results under several simulation conditions by COMPASi and evaluation results by the instructor has strongly implied that the tolerance for the variability of situations might be a major factor in selection of control strategies by a controller. These contributions of the present research may be useful for practical purposes such as further improvement of education and training for controllers.     

Cognitive model of team cooperation in en-route air traffic control

Since controller teams are in charge of en-route air traffic control, team cooperation is a key issue for good control performance. We conducted ethnographic field observation at the Tokyo Area Control Center and then analyzed the obtained data to develop a cognitive model of team cooperation in en-route air traffic control. We segmented conversational records, behavioral records, and so on by control unit, and then clarified relations between the segments and identified expert knowledge and judgment behind them. Cognitive processes of controller teams were reconstructed based on a concept of distributed cognition. The analysis revealed that the mutual belief model is applicable to team cooperation processes, the role assignment of tasks within a controller team is implicit and that control plans are implemented smoothly once team situation awareness has been established. A cognitive model of controllers?? team cooperation has been constructed based on these findings.     

A visualization tool of en route air traffic control tasks for describing controller’s proactive management of traffic situations

Improvements of aviation systems are now in progress to ensure the safety and efficiency of air transport in response to the rapid growth of air traffic. For providing theoretical and empirical basis for design and evaluation of aviation systems, researches focusing on cognitive aspects of air traffic controllers are definitely important. Whereas various researches from cognitive perspective have been performed in the Air Traffic Control (ATC) domain, there are few researches trying to illustrate ATCO’s control strategies and their effects on task demands in real work situations. The authors believe that findings from these researches can contribute to reveal why ATCOs are capable of handling air traffic safely and efficiently even in the high-density traffic condition. It can be core knowledge for tackling human factors issues in the ATC domain such as development of further effective education and training program of ATCO trainees. However, it is difficult to perform such kinds of researches because identification of ATC task from a given traffic situation and specification of effects of ATCO’s control strategies on task demands requires expert knowledge of ATCOs. The present research therefore aims at developing an automated identification and visualization tool of en route ATC tasks based on a cognitive system simulation of an en route controller called COMPAS (COgnitive system Model for simulating Projection-based behaviors of Air traffic controller in dynamic Situations), developed by the authors. The developed visualization tool named COMPASⁱ (COMPAS in interactive mode) equips a projection process model that can simulate realistic features of ATCO’s projection involving setting extra margins for errors of projection. The model enables COMPASⁱ to detect ATC tasks in a given traffic situation automatically and to identify Task Demand Level (TDL), that is, an ATC task index. The basic validity of COMPASⁱ has been confirmed through detailed comparison between TDLs given by a training instructor and ones by COMPASⁱ in a simulation-based experiment. Since TDL corresponds to demands of ATC tasks, temporal sequences of TDLs can reflect effectiveness of ATCO’s control strategies in terms of regulating task demands. By accumulation and analysis of such kind of data, it may be expected to reveal important aspect of ATCO’s skill for achieving the safety and efficiency of air traffic.     

A teamwork model for understanding an agile team: A case study of a Scrum project

ContextSoftware development depends significantly on team performance, as does any process that involves human interaction.ObjectiveMost current development methods argue that teams should self-manage. Our objective is thus to provide a better understanding of the nature of self-managing agile teams, and the teamwork challenges that arise when introducing such teams.MethodWe conducted extensive fieldwork for 9 months in a software development company that introduced Scrum. We focused on the human sensemaking, on how mechanisms of teamwork were understood by the people involved.ResultsWe describe a project through Dickinson and McIntyre’s teamwork model, focusing on the interrelations between essential teamwork components. Problems with team orientation, team leadership and coordination in addition to highly specialized skills and corresponding division of work were important barriers for achieving team effectiveness.ConclusionTransitioning from individual work to self-managing teams requires a reorientation not only by developers but also by management. This transition takes time and resources, but should not be neglected. In addition to Dickinson and McIntyre’s teamwork components, we found trust and shared mental models to be of fundamental importance.     

Towards Flexible Teamwork in Persistent Teams: Extended Report

Teamwork is a critical capability in multi-agent environments. Many such environments mandate that the agents and agent-teams must be persistent i.e., exist over long periods of time. Agents in such persistent teams are bound together by their long-term common interests and goals. This paper focuses on flexible teamwork in such persistent teams. Unfortunately, while previous work has investigated flexible teamwork, persistent teams remain unexplored. For flexible teamwork, one promising approach that has emerged is model-based, i.e., providing agents with general models of teamwork that explicitly specify their commitments in teamwork. Such models enable agents to autonomously reason about coordination. Unfortunately, for persistent teams, such models may lead to coordination and communication actions that while locally optimal, are highly problematic for the team's long-term goals. We present a decision-theoretic technique based on Markov decision processes to enable persistent teams to overcome such limitations of the model-based approach. In particular, agents reason about expected team utilities of future team states that are projected to result from actions recommended by the teamwork model, as well as lower-cost (or higher-cost) variations on these actions. To accommodate real-time constraints, this reasoning is done in an any-time fashion. Implemented examples from an analytic search tree and some real-world domains are presented.