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

One-track mind: Investigating positive and negative applications of non-technical skills in rail network control

It is not just a rail driver but a "system" that drives a train and network controllers apply non-technical skills to facilitate their role as part of a team. However, because of siloed and distributed working, scenarios exist where network controllers may inadvertently increase operational safety risks. The aim of this study was to generate a better understanding of non-technical skill application in network controllers by identifying which skills and behaviours were associated with problematic ways of working, and which abilities were used to address error-producing scenarios, and thereby reduce risk. Use of a scenario technique and behavioural markers analysis of 61 scenarios generated from 55 network controllers in 8 organisations across Australia and New Zealand revealed a large and diverse application of non-technical skills. Careful consideration must be given to the way in which deficiencies in abilities and skills are addressed. Future research directions are given.

Making safety training stickier: A richer model of safety training engagement and transfer

INTRODUCTION

Compared to other types of occupational training, safety training suffers from several unique challenges that potentially impair the engagement of learners and their subsequent application or "transfer" of knowledge and skills upon returning to the job. However, existing research on safety training tends to focus on specific factors in isolation, such as design features and social support. The aim of this research is to develop an overarching theoretical framework that integrates factors contributing to training engagement and transfer.

METHOD

We conducted a comprehensive qualitative review of safety training research that was published between 2010 and 2020. We searched Web of Science, Scopus, and Google Scholar, yielding 147 articles, and 38 were included. We content analyzed article summaries to arrive at core themes and combined them with contemporary models of general occupational training to develop a rich model of safety training engagement and transfer.

RESULTS

We propose that training engagement is a combination of pre-training factors such as individual, organizational, and contextual factors, that interact with design and delivery factors. Safety training engagement is conceptualized as a three-component psychological state: affective, cognitive, and behavioral. Organizations should prioritize pre-training readiness modules to address existing attitudes and beliefs, optimize the safety training transfer climate, and critically reflect on their strategy to design and deliver safety training so that engagement is maximized.

CONCLUSIONS

There are practical factors that organizations can use before training (e.g., tailoring training to employees' characteristics), during training (e.g., ensuring trainer credibility and use of adult learning principles), and after training (e.g., integrating learned concepts into systems). Practical Applications: For safety training to 'stick,' workers should be affectively, cognitively, and behaviorally engaged in learning, which will result in new knowledge and skills, improvements in attitudes, and new safety behaviors in the workplace. To enable engagement, practitioners must apply adult learning principles, make the training relevant, and tailor the training to the job and individual needs. After training, ensure concepts are embedded and aligned with existing systems and routines to promote transfer.

The Analysis of Occurrences Associated with Air Traffic Volume and Air Traffic Controllers' Alertness for Fatigue Risk Management

Fatigue is an inevitable hazard in the provision of air traffic services and it has the potential to degrade human performance leading to occurrences. The International Civil Aviation Organization (ICAO) requires air navigation services which providers establish fatigue risk management systems (FRMS) based on scientific principles for the purpose of managing fatigue. To develop effective FRMSs, it is important to investigate the relationship between traffic volume, air traffic management occurrences, and fatigue. Fifty-seven qualified ATCOs from a European Air Navigation Services provider participated in this research by providing data indicating their alertness levels over the course of a 24-hour period. ATCOs' fatigue data were compared against the total of 153 occurrences and 962,328 air traffic volumes from the Eurocontrol TOKAI incident database in 2019. The result demonstrated that ATCO fatigue levels are not the main contributory factor associated with air traffic management occurrences, although fatigue did impact ATCOs' performance. High traffic volume increases ATCO cognitive task load that can surpass available attention resources leading to occurrences. Furthermore, human resilience drives ATCOs to maintain operational safety though they suffer from circadian fatigue. Consequently, FRMS appropriately implemented can be used to mitigate the effects of fatigue. First-line countermeasure strategies should focus on enough rest breaks and roster schedule optimization; secondary strategies should focus on monitoring ATCOs' task loads that may induce fatigue. It is vital to consider traffic volume and ATCOs' alertness levels when implementing effective fatigue risk management protocols.

Predicting Air Traffic Controller Workload: Trajectory Uncertainty as the Moderator of the Indirect Effect of Traffic Density on Controller Workload Through Traffic Conflict

OBJECTIVE

Our study investigates whether trajectory uncertainty moderates the relationship between traffic conflict and workload. Furthermore, we examine if the indirect effect of traffic density on workload through traffic conflict is conditional on the presence of trajectory uncertainty.

BACKGROUND

Although it is widely accepted that uncertainty related to the future trajectory of an aircraft impacts air traffic controller decision making, little is known about how the presence of trajectory uncertainty impacts controller workload. A better understanding of the impact on controller workload can improve workload prediction models for en route air traffic control.

METHOD

We collected data in a live operation environment, including workload ratings based on over-the-shoulder observations and real-time sector data. Hierarchical linear modeling was used to analyze the data.

RESULTS

Trajectory uncertainty interacts with traffic conflict in such a way that the positive relationship between traffic conflict and workload is strongest in the presence of trajectory uncertainty. Furthermore, we found that the mediating effect of traffic density through traffic conflict is conditional on the presence of trajectory uncertainty.

CONCLUSION

Our results indicate that workload prediction tools that do not incorporate trajectory uncertainty may underestimate workload under conditions of trajectory uncertainty, leading to possible overload situations of air traffic controllers.

APPLICATION

Sources that generate trajectory uncertainty, as well as their interaction effects with dynamic complexity metrics, should be acknowledged in workload prediction models to increase the predictive power of these models. Implications for future air traffic management operations as envisioned by SESAR and NextGen are discussed.

Development and validation of a multilevel model for predicting workload under routine and nonroutine conditions in an air traffic management center

OBJECTIVE

The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions.

BACKGROUND

Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem.

METHOD

A multilevel workload model was developed in Study I with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters.The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator.

RESULTS

Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically.

CONCLUSION

The model performed well under both routine and nonroutine conditions and over different patterns of workload variation.

APPLICATION

Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs.Tactical uses include the dynamic reallocation of resources to meet changes in demand.

Resilient actions in the diagnostic process and system performance

OBJECTIVES

Systemic issues can adversely affect the diagnostic process. Many system-related barriers can be masked by 'resilient' actions of frontline providers (ie, actions supporting the safe delivery of care in the presence of pressures that the system cannot readily adapt to). We explored system barriers and resilient actions of primary care providers (PCPs) in the diagnostic evaluation of cancer.

METHODS

We conducted a secondary data analysis of interviews of PCPs involved in diagnostic evaluation of 29 lung and colorectal cancer cases. Cases covered a range of diagnostic timeliness and were analysed to identify barriers for rapid diagnostic evaluation, and PCPs' actions involving elements of resilience addressing those barriers. We rated these actions according to whether they were usual or extraordinary for typical PCP work.

RESULTS

Resilient actions and associated barriers were found in 59% of the cases, in all ranges of timeliness, with 40% involving actions rated as beyond typical. Most of the barriers were related to access to specialty services and coordination with patients. Many of the resilient actions involved using additional communication channels to solicit cooperation from other participants in the diagnostic process.

DISCUSSION

Diagnostic evaluation of cancer involves several resilient actions by PCPs targeted at system deficiencies. PCPs' actions can sometimes mitigate system barriers to diagnosis, and thereby impact the sensitivity of 'downstream' measures (eg, delays) in detecting barriers. While resilient actions might enable providers to mitigate system deficiencies in the short run, they can be resource intensive and potentially unsustainable. They complement, rather than substitute for, structural remedies to improve system performance. Measures to detect and fix system performance issues targeted by these resilient actions could facilitate diagnostic safety.

A sensemaking perspective on framing the mental picture of air traffic controllers

It has long been recognized that controller strategies are based on a 'mental picture' or representation of traffic situations. Earlier studies indicated that controllers tend to maintain a selective representation of traffic flows based on a few salient traffic features that point out to interesting events (e.g., potential conflicts). A field study is presented in this paper that examines salient features or 'knowledge variables' that constitute the building blocks of controller mental pictures. Verbal reports from participants, a field experiment and observations of real-life scenarios provided insights into the cognitive processes that shape and reframe the mental pictures of controllers. Several cognitive processes (i.e., problem detection, elaboration, reframing and replanning) have been explored within a particular framework of sensemaking stemming from the data/frame theory (Klein et al., 2007). Cognitive maps, representing standard and non-standard air traffic flows, emerged as an explanatory framework for making sense of traffic patterns and for reframing mental pictures. The data/frame theory proved to be a useful theoretical tool for investigating complex cognitive phenomena. The findings of the study have implications for the design of training curricula and decision support systems in air traffic control systems.

Railway-controller-perceived competence in incidents and accidents

Railway controllers play a pivotal role in service recovery of normal rail system operations when incidents and accidents occur. Those in this position must have sufficient competence to overcome task difficulties caused by accident uncertainties. This study adopts Taiwan's railway system as a case study to diagnose railway-controller-perceived competence when facing diverse tasks during incidents and accidents that are derived from a proposed conceptual model. Railway-controller-perceived competence is measured using the Rasch model. Analytical results indicate that working with an external rescue agency handling a rescue operation, explanations to the public, and communication with an external rescue agency are considered the most troublesome tasks. Additionally, railway-controller-perceived competence differs based on the work experience. This information will prove useful for rail system operators and government regulators when designing and regulating railway controller competence management systems. STATEMENT OF RELEVANCE: This study presents a systematic approach for examining the gap between railway-controller-perceived competence and task difficulties associated with incidents and accidents. The relevance of findings encompasses the effects of transportation ergonomics and railway issues on the problem-solving competence and decision-making skills of railway controllers, and the competence management system.

A systems perspective of managing error recovery and tactical re-planning of operating teams in safety critical domains

INTRODUCTION

Research in human error has provided useful tools for designing procedures, training, and intelligent interfaces that trap errors at an early stage. However, this "error prevention" policy may not be entirely successful because human errors will inevitably occur. This requires that the error management process (e.g., detection, diagnosis and correction) must also be supported. Research has focused almost exclusively on error detection; little is known about error recovery, especially in the context of safety critical systems. The aim of this paper is to develop a research framework that integrates error recovery strategies employed by experienced practitioners in handling their own errors.

METHOD AND RESULTS

A control theoretic model of human performance was used to integrate error recovery strategies assembled from reviews of the literature, analyses of near misses from aviation and command & control domains, and observations of abnormal situations training at air traffic control facilities. The method of system dynamics has been used to analyze and compare error recovery strategies in terms of patterns of interaction, system affordances, and types of recovery plans. System dynamics offer a promising basis for studying the nature of error recovery management in the context of team interactions and system characteristics.

IMPACT ON INDUSTRY

The proposed taxonomy of error recovery strategies can help human factors and safety experts to develop resilient system designs and training solutions for managing human errors in unforeseen situations; it may also help incident investigators to explore why people's actions and assessments were not corrected at the time.