Low Situation Awareness Research Articles

Can Proficiency in Chess Predict Situation Awareness in a Novel Task?

This study explored the correlation between situation awareness (SA) and proficiency in chess. Eighteen participants were tested, performing a letter factory (LF) task and providing their ELO scores. Each participant received $10 for 30 min of participation. The results showed a negative correlation between the number of games played and the SA score, suggesting that increased gameplay was associated with lower SA in the letter factory task. Additionally, the ELO score was negatively correlated with the number of double attempts to place a designated letter in the loading boxes, indicating that more skilled players made fewer errors.

Exploring construction workers' attention and awareness in diverse virtual hazard scenarios to prevent struck-by accidents

Repetitive tasks in construction reduce workers' attentiveness of hazards on sites. This decline in attentiveness can be influenced by their situation awareness level. However, research on the relationship between attentiveness and situation awareness is scarce in the construction safety domain. This study employs eye-tracking techniques to investigate how visual attention changes due to variations in workers’ situation awareness levels. A virtual reality-based experiment was conducted to evaluate the situation awareness level of individual workers and examine its relationship with attentiveness towards different hazards using the situation awareness global assessment technique and linear regression analysis. The experimental findings reveal that the overall trend of allocating attention toward hazards declined over time. Furthermore, the attentiveness of workers varied depending on their situation awareness levels and the type of hazardous condition. Throughout the experiment, the group with a low situation awareness failed to sustain their vigilance toward hazards as effectively as the group with a high situation awareness. The outcomes of this study will help construction safety trainers understand variations in workers' vigilance behavior over time and, thus mitigate the risk of accidents owing to inattentiveness at job sites.

Recognizing the situation awareness of forklift operators based on EEG techniques in a field experiment.

Lack of situation awareness (SA) is the primary cause of human errors when operating forklifts, so determining the SA level of the forklift operator is crucial to the safety of forklift operations. An EEG recognition approach of forklift operator SA in actual settings was presented in order to address the issues with invasiveness, subjectivity, and intermittency of existing measuring methods. In this paper, we conducted a field experiment that mimicked a typical forklift operation scenario to verify the differences in EEG states of forklift operators with different SA levels and investigate the correlation of multi-band combination features of each brain region of forklift operators with SA. Based on the sensitive EEG combination indexes, Support Vector Mechanism was used to construct a forklift operator SA recognition model. The results revealed that there were differences between forklift operators with high and low SA in the θ, α, and β frequency bands in zones F, C, P, and O; combined EEG indicators θ/β, (α + θ)/(α + β), and θ/(α + β) in zones F, P, and C were significantly correlated with SA; the recognition accuracy of the model reached 88.64% in the case of combined EEG indicators of zones C & F & P as input. It could provide a reference for SA measurement, contributing to the improvement of SA.

EEG-based analysis for pilots' at-risk cognitive competency identification using RF-CNN algorithm.

Cognitive competency is an essential complement to the existing ship pilot screening system that should be focused on. Situation awareness (SA), as the cognitive foundation of unsafe behaviors, is susceptible to influencing piloting performance. To address this issue, this paper develops an identification model based on random forest- convolutional neural network (RF-CNN) method for detecting at-risk cognitive competency (i.e., low SA level) using wearable EEG signal acquisition technology. In the poor visibility scene, the pilots' SA levels were correlated with EEG frequency metrics in frontal (F) and central (C) regions, including α/β (p = 0.071 < 0.1 in F and p = 0.042 < 0.05 in C), θ/(α + θ) (p = 0.048 < 0.05 in F and p = 0.026 < 0.05 in C) and (α + θ)/β (p = 0.046 < 0.05 in F and p = 0.012 < 0.05 in C), and then a total of 12 correlation features were obtained based on a 5 s sliding time window. Using the RF algorithm developed by principal component analysis (PCA) for further feature combination, these salient combinations are used as input sets to obtain the CNN algorithm with optimal parameters for identification. The comparative results of the proposed RF-CNN (accuracy is 84.8%) against individual RF (accuracy is 78.1%) and CNN (accuracy is 81.6%) methods demonstrate that the RF-CNN with feature optimization provides the best identification of at-risk cognitive competency (accuracy increases 6.7%). Overall, the results of this paper provide key technical support for the development of an adaptive evaluation system of pilots' cognitive competency based on intelligent technology, and lay the foundation and framework for monitoring the cognitive process and competency of ship piloting operation in China.

Recognising situation awareness associated with different workloads using EEG and eye-tracking features in air traffic control tasks

The rate of human errors would increase as air traffic control officers (ATCOs) lose situation awareness (SA), which could also be affected by their perceived workloads. Recognising ATCOs SA inadequacy is crucial for ensuring traffic safety. This paper aims to propose a two-phase analytical methodology for revealing SA-related neuro-physiological patterns and hierarchically recognising ATCOs SA loss with workload concerns using EEG and eye-tracking data. A simulated air traffic control (ATC) radar-monitoring experiment involving different task loads with SA-probe tests was first conducted to collect behavioural and physiological (EEG and eye-tracking) data simultaneously, and the NASA Task Load Index (NASA-TLX) scale was used to measure participants’ perceived workloads. In our two-phase methodology, behavioural data representing the task performance was analysed in Phase I using the Gaussian Mixture Model to determine sample’s SA, and the perceived workloads on samples were labelled using NASA-TLX scores. Subsequently, in order to achieve our purposes, the physiological data were annotated based on results from Phase I, the physiological feature base was extracted using a fast Fourier transformation and Hilbert transform in Phase II, and the linear discriminant analysis was then used to extract the core features as inputs to train multiple classifiers. Results showed that the neuro-physiological behaviours of SA loss during normal workloads differed from those in high workload situations. A leave-one-subject-out cross-validation was also performed, and the results demonstrated that the optimal performance was 76.1% for classifying high/low SA (1-Level classification) and 82.7% for recognising low SA associated with high workload (2-Level classification).

Assessing the potential impacts of connected vehicle systems on Driver’s situation awareness and driving performance

Vehicles equipped with connected vehicle technologies are able to communicate with each other and with infrastructures. Compared to Advanced Driving Assistance Systems (ADAS) using camera systems and sensor technologies, the Connected Vehicle Systems (CVS) leverage the wireless communication networks to detect hazards with a greater range, alert drivers of hazards much earlier, and therefore enhance driving safety. However, drivers’ reliance on the CVS to detect critical situations could negatively affect them maintaining situation awareness (SA) in noncritical situations when no warning is issued by the CVS. The present study conducted a driving simulator experiment with 40 participants to investigate the effect of connected vehicle systems on driver SA in normal, noncritical driving scenarios after they were exposed to the CVS with different designs of collision warning lead time (3 s, 6 s, and no warnings). After drivers experienced the CVS-supported warnings with the assigned design of lead time in critical situations, driver SA was measured in normal driving conditions using the freeze probe technique. Results revealed that drivers who experienced the CVS with early warnings (6 s) showed lower SA for normal driving events compared to those who experienced the CVS with late warnings (3 s) or no warnings. Although early warnings of CVS brought more safety benefits to drivers in critical situations, the degraded driver SA due to drivers’ reliance on such warning systems could endanger drivers when a system failure occurred. These findings highlight the importance of balancing the effects of warning lead time on driver SA and driving performance in designing connected vehicle systems.

An approach to situation awareness (SA) assessment in flight simulation: SA dynamic circulation (SADC) model

AbstractAccurate prediction and evaluation of pilot's situation awareness (SA) are of great importance for ensuring flight safety. In the present study, an SA dynamic circulation (SADC) model is developed for describing the dynamic generation and update processes of pilot's SA in‐flight environments. In the SADC model, five cognitive statuses of SA, which constitute the dynamic circulation in a closed‐loop network, are put forward on a framework of adaptive control of thought rational‐queuing network. By introducing the progressive triggers of the low and high SA, pilot's SA covering three levels is computed using conditional probability. In addition, flight simulations based on four typical flight scenarios were performed to verify the usability of the SADC model, and multiple methods including the subjective evaluation, situation present assessment method (SPAM), and physiological measurement were adopted for SA measurement. According to the results, the rationality of the SADC model is validated due to the significant correlations between SA theoretical prediction value and SPAM response time as well as 10D‐SART score. Besides, in our study, the SPAM response time and 10D‐SART score show an acceptable sensitivity to SA measurement, however, physiological indicators of respiratory rate and standard deviation of normal to normal RR intervals are proved more sensitive to workload rather than SA. The SADC model is expected to be applied in the quantitative characterization of pilot's SA as a new auxiliary analysis tool during cockpit display interface design and flight training strategy optimization.

Correlation Evaluation of Pilots' Situation Awareness in Bridge Simulations via Eye-Tracking Technology.

To maintain situation awareness (SA) when exposed to emergencies during pilotage, a pilot needs to selectively allocate attentional resources to perceive critical status information about ships and environments. Although it is important to continuously monitor a pilot's SA, its relationship with attention is still not fully understood in ship pilotage. This study performs bridge simulation experiments that include vessel departure, navigation in the fairway, encounters, poor visibility, and anchoring scenes with 13 pilots (mean = 11.3 and standard deviation = 1.4 of experience). Individuals were divided into two SA group levels based on the Situation Awareness Rating Technology (SART-2) score (mean = 20.13 and standard deviation = 5.83) after the experiments. The visual patterns using different SA groups were examined using heat maps and scan paths based on pilots' fixations and saccade data. The preliminary visual analyses of the heat maps and scan paths indicate that the pilots' attentional distribution is modulated by the SA level. That is, the most concerning areas of interest (AOIs) for pilots in the high and low SA groups are outside the window (AOI-2) and electronic charts (AOI-1), respectively. Subsequently, permutation simulations were utilized to identify statistical differences between the pilots' eye-tracking metrics and SA. The results of the statistical analyses show that the fixation and saccade metrics are affected by the SA level in different AOIs across the five scenes, which confirms the findings of previous studies. In encounter scenes, the pilots' SA level is correlated with the fixation and saccade metrics: fixation count (p = 0.034 < 0.05 in AOI-1 and p = 0.032 < 0.05 in AOI-2), fixation duration (p = 0.043 < 0.05 in AOI-1 and p = 0.014 < 0.05 in AOI-2), and saccade count (p = 0.086 < 0.1 in AOI-1 and p = 0.054 < 0.1 in AOI-2). This was determined by the fixation count (p = 0.024 < 0.05 in AOI-1 and p = 0.034 < 0.05 in AOI-2), fixation duration (p = 0.036 < 0.05 in AOI-1 and p = 0.047 < 0.05 in AOI-2), and saccade duration (p = 0.05 ≤ 0.05 in AOI-1 and p = 0.042 < 0.05 in AOI-2) in poor-visibility scenes. In the remaining scenes, the SA could not be measured using eye movements alone. This study lays a foundation for the cognitive mechanism recognition of pilots based on SA via eye-tracking technology, which provides a reference to establish cognitive competency standards in preliminary pilot screenings.

Eye tracking data analytics in virtual reality training: Application in Deepwater Horizon oil drilling operation

Virtual reality (VR) enable us to train in a safe environment using computer-generated simulations. One such simulated environment is the Deepwater Horizon operation, and VR enables us to evaluate trainees’ and operators’ situation awareness (SA) in a non-hazardous environment. One unobtrusive and viable SA evaluation method might be the use of eye movements, specifically the time-ordered visual scan paths. In this research, we investigated how SA can be associated with visual scan paths in an anomaly detection task within the oil drilling rig virtual reality simulator. The results show that the trainees having lower SA tended to create random visual scan paths whereas the trainees having higher SA tended to create concentrated and refined visual scan paths. The results show promise in developing timely intervention methods through analyzing the visual scan path characteristics of the trainees.

The importance of domain-dependent cognitive factors in GA safety: Predicting critical incidents with prospective memory, situation awareness, and pilot attributes

General aviation (GA) has been described as the incubator for almost all civil aviation operations, yet the GA safety record is consistently poor in comparison to airline operations. To identify the human factors associated with GA safety, eight distinct predictive factors, representing prospective memory, situation awareness (SA), and pilot age and expertise, were investigated for their relationship to critical incidents. Ninety-two licensed pilots flew patterns at two aerodromes in a high-fidelity Cessna 172 simulator. Greater likelihood of incurring a critical incident was associated with lower prospective memory and lower SA. Pilots with lower levels of expertise and older age were also more likely to have experienced a critical incident. Our findings highlight multiple cognitive factors associated with critical incidents during GA flight. In particular, stakeholders in aviation safety should incorporate indices of prospective memory when developing and testing pilot competencies, as this variable showed the strongest link to critical incidents. Furthermore, prospective memory and SA mediated some of the effects of age and expertise on critical incidents, suggesting that strategies to enhance prospective memory and SA may attenuate the deleterious impact of older age and lower experience on GA safety.

Workflow disruptions and provider situation awareness in acute care: An observational study with emergency department physicians and nurses

BackgroundThe fast-paced and rapidly changing environment of an Emergency Department (ED) requires providers to have a high level of situation awareness (SA). However, acute clinical care also encompasses a multitude of interruption-laden work processes that might degrade SA. It is therefore important to understand how frequent interruptions affect ED provider cognition in general and SA in particular. ObjectiveWe aimed to examine how sources and contents of provider workflow interruptions influence situation awareness of ED physicians and nurses. MethodsThis prospective, multi-method study combined standardized observations, self-reports of ED providers, and ED administrative data of staffing and patient load. Expert observers identified ED providers’ workflow interruptions during 90min observation sessions. Afterwards, each provider reported perceived disruptiveness and situation awareness. Controlling for patient load, patient acuity and staffing, we conducted regression analyses to explore prospective associations between interruptions and provider outcomes. ResultsDuring 74 observation sessions of overall 110h and 40min, we observed 1205 workflow interruptions (mean rate: 10.9 interruptions/hour). Provider situation awareness was fairly high (M = 7.10; scale 0–10) with no difference between ED physicians and nurses. After controlling for ED workload data, we observed that high rates of interruptions were associated with lower levels of situation awareness (β = −0.27). Further analyses revealed that particularly interruptions by telephone/beeper, technical malfunctions as well as interruptive communication related to completed cases were correlated to low SA. DiscussionThis study in a naturalistic ED setting shows that ED physicians and nurses continuously cope with disruptions and interruptions. Our findings reveal that highly interruptive workflow environments impede providers' situation awareness. Moreover, it sheds light on specific sources and contents of interruptions that influence providers’ SA in acute care. ConclusionFrequent workflow interruptions can degrade ED providers’ situation awareness. A deeper understanding of how avoidable and unavoidable interruptions affect provider cognitions with particular focus on social and technology-related disruptions is required. Further emphasis should be placed on the effective application of work re-design in this context to foster safe and efficient patient care.

VR-Based investigation of forklift operator situation awareness for preventing collision accidents

Forklifts are among the machines involved with the highest levels of occupational fatalities. As many accidents involved with a forklift can be attributed to the low situation awareness (SA) of the operator, it is essential to understand the factors influencing a forklift operator’s SA for reducing forklift accidents, especially of collision type. Against this background, this research aims to investigate how a forklift operator’s SA about other people around can be influenced by the type of subtasks they are carrying out. In this research, a virtual reality (VR) environment is used as the experiment environment, in which subjects perform a series of subtasks, such as driving, turning, reversing, loading and unloading, with a VR forklift simulation model. A SAGAT—an established SA measurement technique based on a series of queries targeting Level 1, 2, and 3 SA—is used as the main method to collect data about subjects’ SA in the experiment. The analysis of the data reveals that a forklift operator is likely to have a reduced SA about the workers around when he/she is performing a loading or unloading task due to attention narrowing, which occurs when a person concentrates on a cognitively demanding task. The findings provide insights into how forklift operator SA could be improved through an SA-oriented safety training program and also how sensing technologies might assist forklift operators with maintaining a good SA.

EEG-Based Analysis of Air Traffic Conflict: Investigating Controllers’ Situation Awareness, Stress Level and Brain Activity during Conflict Resolution

The effects of air traffic conflict geometry have been well investigated in prior studies, particularly in the context of the pilot, though little in the context of the air traffic control officer (ATCO). No study to date has investigated the effects of conflict geometry on human factors variables of ATCOs through objective and physiological approaches. This study examines the effects of conflict geometries on ATCO situation awareness, stress level and brain activity during conflict resolution. Fifteen participants were instructed to resolve six different conflict geometries: crossing level, crossing non-level, converging level, converging non-level, overtaking level, and overtaking non-level. The results indicate that converging and crossing conflicts led to lower situation awareness (SA), higher stress level, and higher theta activation at the temporal and parietal lobes. Level conflict led to lower SA. The findings offer two implications, providing insights for the formal guidelines in ATC conflict resolution training and provision of inputs for the conflict resolution aid development.

Situation Awareness Analysis on Motorcycle Riders using Quantitative Analysis of Situational Awareness

A Traffic accident is caused by the negligence and the low situation awareness of the motorcycle riders. Based on the Indonesian Police traffic data, until May 2018, there were 32,127 motorcycle accidents with 6,009 people died. The highest accidents happened to the riders between 15-19 years old. Thus, feasibility of the motorcycle riders becomes crucial. The purpose of this study is to determine the level of awareness of the motorcycle riders as well as to determine the minimum age level to ride motorcycle. There were 75 respondents participating in this study who were about 17 to 19 years old. The Quantitative Analysis of Situational Awareness method was used to achieve the objective. The results of this study show that 17 years old riders have better situation awareness level than 18 years old ones. Meanwhile, the best situation awareness level is at age 19. It is because of the value of calibration (12.22%) which is smaller than 17 years old (17.52%) and 18 years old riders (26.48%). Therefore, this study recommends the feasibility of motorcycle riders should be 19 years old as the minimum requirement.

Perceived stress in human-machine interaction in modern manufacturing environments-Results of a qualitative interview study.

Rapid advances in digitization technologies are changing modern working conditions especially in industrial settings. Consequently, employees are confronted with new forms of human-machine interaction. Whether changes in working conditions in general, and the increasing relevance of human-machine interaction in particular, affect psychosocial working conditions, and employee's health is currently matter of debate, but empirical data are lacking. Therefore, we conducted semistructured interviews with 36 employees working in five different companies. The interviews were aimed at identifying potential stressors associated with the introduction and use of modern technologies in the manufacturing industry. The results show that stressors linked to human-machine interaction are technical problems, poor usability, low situation awareness, and increased requirements on employees' qualification. For example, technical problems such as breakdowns or slowdowns were described as a main stressor when employees were not qualified to handle these problems on their own, thus decelerating work flows and causing additional time pressure. Overall, the results show that problems in human-machine interaction, which have been observed in laboratory and nonindustrial settings, also apply to industrial work places with highly automated working conditions and are a potential source of stress. These factors should be considered in psychosocial risk assessment of work-related stressors.

Operator situation awareness and physiological states during offshore well control scenarios

Incident reviews of oil spill events (both large and small) suggest that human error is a contributor to 50% of well control incidents (primarily kicks). The purpose of this study was to examine operator situation awareness (SA) and associated physiological load, using heart rate and heart rate variability (HRV), during different simulated offshore well control scenarios (drilling and tripping) and criticality levels (failure presented or not). Ten trained participants completed four scenarios (tripping non-failure, tripping failure, drilling non-failure, and drilling-failure) in an experimental session, lasting ∼6 h. Measures were obtained for each scenario, including speed and accuracy of the task performance, composite scores obtained from the Situational Awareness Rating Technique (SART), and operator heart rate and heart rate variability measures. Greater errors were found in kick-related failure events, and drilling scenarios were associated with longer reaction times. Participants perceived lower SA levels during drilling scenarios, and the was observed for lowest SA during drilling failure scenarios. Finally, while physiological responses did not differ significantly for any of the four scenarios, elevated heart rate was observed with drilling and failure-related scenarios. High variability in participant covert and overt responses may increase the challenges associated with classifying high-risk well control scenarios. It is critical that scenario planners understand and recognize the variability in driller situation awareness and associated physiological load when planning for alternative future scenarios.

Using Situation Awareness and Workload to Predict Performance in Submarine Track Management: A Multilevel Approach.

Examine the extent to which subjective workload and situation awareness (SA) can predict variance in performance at the between- and within-person levels of analysis in a simulated submarine track management task. SA and workload are crucial constructs in human factors that are conceptualized as states that change within individuals over time. Thus, a change in an individual's subjective workload or SA over the course of performing a task should be predictive of their subsequent performance (within-person effects). However, there is little empirical evidence for this. Participants monitored displays to track the behaviors of contacts in relationship to their own ship (Ownship) and landmarks. The Situational Awareness Global Assessment Technique measured SA, and the Air Traffic Workload Input Technique measured subjective workload. When a participant's subjective workload rating increased, their subsequent performance decreased, but there was no evidence for within-person effects of SA on performance. We replicated prior between-person level effects of SA; participants with higher SA performed better than those with lower SA. Change in an individual's subjective workload rating (but not SA) was predictive of their subsequent performance. Because an increase in SA should increase the extent to which operators hold the knowledge required to perform subsequent tasks, further research is required to examine SA effects on performance at the within-person level. Adapting automation is more likely to produce optimal outcomes if based on measurement of operator states that predict future task performance, such as workload.

Ambulatory Clinic Exam Room Design with respect to Computing Devices: A Laboratory Simulation Study

OCCUPATIONAL APPLICATIONS When comparing a typical exam room layout to the Department of Veterans Affairs (VA's) new exam room design, with respect to the exam room computing, primary care providers experienced significantly less mental workload and greater situation awareness when using the new exam room design. Further, providers rated the new exam room layout significantly higher in terms of being integrated with their clinical workflow and spent significantly more time in screen sharing activities with the patient. A more thoughtful design of the exam room layout with respect to the placement and physical design of the computing set-up may reduce provider cognitive effort and enhance aspects of patient centeredness by viewing the computer and electronic health record (EHR) it displays as an important mediator between provider and patient. This was achieved by using an all-in-one computer attached to a wall mount that moves the monitor along three axes, allowing for optimal screen positioning and adjustable depending upon the scenario.TECHNICAL ABSTRACT Background: Challenges persist regarding how to integrate computing effectively into the exam room, while maintaining patient-centered care. Purpose: Our objective was to evaluate a new exam room design with respect to the computing layout, which included a wall-mounted monitor for ease of (re)-positioning. Methods: In a lab-based experiment, 28 providers used prototypes of the new and older “legacy” outpatient exam room layouts in a within-subject comparison using simulated patient encounters. We measured efficiency, errors, workload, patient-centeredness (proportion of time the provider was focused on the patient), amount of screen sharing with the patient, workflow integration, and provider situation awareness. Results: There were no statistically significant differences between the exam room layouts for efficiency, errors, or time spent focused on the patient. However, when using the new layout providers spent 75% more time in screen sharing activities with the patient, had 31% lower workload, and gave higher ratings for situation awareness (14%) and workflow integration (17%). Conclusions: Providers seemed to be unwilling to compromise their focus on the patient when the computer was in a fixed position in the corner of the room and, as a result, experienced greater workload, lower situation awareness, and poorer workflow integration when using the old “legacy” layout. A thoughtful design of the exam room with respect to the computing may positively impact providers' workload, situation awareness, time spent in screen sharing activities, and workflow integration.

Change detection support for supervisory controllers of highly automated systems: Effects on performance, mental workload, and recovery of situation awareness following interruptions

Dynamic Positioning (DP) is a computer-controlled process to automatically keep a floating vessel at a specific position or to follow a pre-defined path (tracking) by using its own propellers and thrusters. The human supervisory controller has no direct need to constantly know what the status is of all parts of the automation and the system it is controlling, because the highly automated DPS is controlling all components itself. Only after a failure arises, the operator needs to take over manual control and take appropriate action(s) to prevent the failure from harming the operation. As the supervisory controller may be out of the loop, swiftly taking over control may be problematic when failures arise. The purpose of the current study was to investigate whether automation of change detection enables human operators with low awareness of the automation and the system it is controlling to quickly recover awareness in emergency take-over situations. A 2 by 2 within subjects experiment was conducted using a DP simulation (n = 22). Within-subjects factors were support (Yes, No) and interruption (Yes, No). Results showed that change detection support helps in the process of recovering situation awareness after it has been reduced, due to an interruption of the primary task of overseeing the automation. Interestingly, support was not beneficial to the participants in all conditions. In non-interrupted conditions the support unexpectedly resulted in higher workload, raising questions whether supervisory controllers should be supported continuously or only when it is required. Relevance to industry: The results show that change detection support has potential value in operational maritime environments, especially in situations where the DP operator has low situation awareness. Future research should investigate whether adaptive aiding could alleviate some of the negative effects of non-adaptive operator support in maritime environments.

Explicit or implicit situation awareness? Measuring the situation awareness of train traffic controllers

Previous research on situation awareness (SA) predominantly focused on its explicit, reasoned, conscious features rather than on the implicit, intuitive, unconscious aspects that are often identified with expert operators. This research investigated implicit levels of SA of train traffic controllers (TTCs) in order to contribute to the body of knowledge on rail human factors research and SA. A novel approach was used to uncover levels of implicit SA through a set of three analyses: (1) fairly low SAGAT values with correlations between SAGAT scores and multiple performance indicators; (2) negative correlations between work experience and SAGAT scores; and (3) structurally lower level-1 SA (perception) scores in comparison to level-2 SA (comprehension) scores in accordance with Endsley’s three-level model. Two studies were conducted: A pilot study – which focused on SA measurements with TTCs in a monitoring mode (N=9) – and the main study, which involved TTCs from another control center (N=20) and three different disrupted conditions. In the pilot study, SA was measured through the situation-awareness global assessment technique (SAGAT), perceived SA and observed SA, and performance was measured through punctuality and unplanned stops of trains before red signals. In the main study, SA was measured through SAGAT, and perceived SA and multiple performance indicators, such as arrival and departure punctuality and platform consistency, were assessed. In both studies, the set of three analyses showed consistent and persistent indications of the presence of implicit SA. Endsley’s three-level model and related SAGAT method can be constrained by the presence of these intuitive, unconscious processes and inconsistent findings on correlations between SAGAT scores and performance. These findings provide insights into the SA of TTCs in the Netherlands and can support the development of training programs and/or the design of a new traffic management system.