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This study highlights the disproportionate number of fatal and non-fatal accidents in general aviation (GA) compared to airline carriers, emphasizing the need to investigate the contributing factors to these incidents. It identifies poor decision-making and a lack of situational awareness as key issues and presents a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to analyze preflight information used by GA pilots. The findings underscore the significance of operational factors in ensuring a successful flight and suggest modifications to pilot license renewal processes, with an emphasis on the adoption of digital preflight tools. A new theoretical framework based on the operational factors identified is also introduced, which could serve as a foundation for future studies and interventions aimed at enhancing safety in general aviation. [ABSTRACT FROM AUTHOR]

Objective: Situation awareness (SA) refers to people's perception and understanding of their dynamic environment. In primary care, reduced SA among physicians increases errors in clinical decision-making and, correspondingly, patients' risk of experiencing adverse outcomes. Our objective was to understand the extent to which electronic health records (EHRs) support primary care physicians (PCPs)' SA during clinical decision-making. Method: We conducted a metanarrative review of papers in selected academic databases, including CINAHL and MEDLINE. Eligible studies included original peer-reviewed research published between January 2012 and August 2020 on PCP–EHR interactions. We iteratively queried, screened, and summarized literature focused on EHRs supporting PCPs' clinical decision-making and care management for adults. Then, we mapped findings to an established SA framework to classify external factors (individual, task, and system) affecting PCPs' levels of SA (1–Perception, 2–Comprehension, and 3–Projection) and identified SA barriers. Results: From 1504 articles identified, we included and synthesized 19 studies. Study designs were largely noninterventional. Studies described EHR workflow misalignments, usability issues, and communication challenges. EHR information, including lab results and care plans, was characterized as incomplete, untimely, or irrelevant. Unmet information needs made it difficult for PCPs to obtain even basic SA, Level 1 SA. Prevalent barriers to PCPs developing SA with EHRs were errant mental models, attentional tunneling, and data overload. Conclusion: Based on our review, EHRs do not support the development of higher levels of SA among PCPs. Review findings suggest SA-oriented design processes for health information technology could improve PCPs' SA, satisfaction, and decision-making. [ABSTRACT FROM AUTHOR]

Background: An important factor in preventing industrial accidents includes the ability of employees to have awareness of the work situation, understand the information from it, and predict how situations will develop. In this study, we examined the role of fatigue and work-related stress in predicting work situation awareness among workers. Methods: The current study was a cross-sectional study. The sample consisted of 180 employees in the National Petrochemical Company in 2022 year that was selected according to the stratified random sampling method and responded to questionnaires about demographic characteristics, work situation awareness, work stress, and fatigue. The data were analyzed by correlation techniques and stepwise regression. Results: The results showed that there was a significant internal correlation between research variables. Also, the results of stepwise regression analysis revealed that fatigue and work stress significantly predicted, respectively, almost 11% and 16% of variances in work situation awareness among workers. Conclusion: According to the findings of the present study, fatigue and work-related stress can predict work situation awareness. Therefore, considering these variables can be significant in promoting work situation awareness among workers. [ABSTRACT FROM AUTHOR]

Forklift drivers in in-house logistics are at a high risk of occupational injuries. This study piloted a video-based learning game for forklift drivers, designed to increase their safety awareness in their highly dynamic operating environment. The game consisted of video clips filmed from the driver's perspective. Each video clip was stopped and masked at a point where a safety-relevant item or hazard appeared. Two locations were marked on the screen, one with the hazard and the other with no hazard. The players had to choose the location with the hazard while the screen was masked and received feedback on their choice. Eighty-one professional forklift drivers played the game at their workplaces during the 3–4 month intervention. In addition, forklift registered hard shocks were recorded and compared to the game performance of 20 participants. Higher accuracy in the game correlated with a lower shock rate, suggesting that real-world forklift driving skills transferred to the game. However, accuracy improvement in the game did not decrease the vehicle registered hard shocks. During the intervention, 40% of the participants reported that they began to pay more attention to the hazards of their work environment. Overall, the results suggest that a gamified approach could be useful for demonstrating safety-relevant features at the workplace and supporting drivers' safety-related self-reflection. [ABSTRACT FROM AUTHOR]

• Autonomous ships expected to adopt artificially intelligent agents for navigation. • Human supervision anticipated to assure safe performance, but support needed. • Requirements for agent information disclosure defined using cognitive task analysis. • Insight into agent internal reasoning gives understandability and predictability. • Affording humans with agent transparency supports safe and effective supervision. Ongoing trends in society point towards the adoption of intelligent agents across safety critical industries. In the maritime domain, artificially intelligent agents may soon be capable of autonomously performing collision and grounding avoidance (CAGA); a task traditionally performed by humans. Consequently, the role of humans is anticipated to change from those performing collision avoidance to those supervising an agent performing collision avoidance. One of the key concerns with regards to human factors is avoiding the out-of-the-loop performance problem where humans lose situation awareness (SA) and become susceptible to misinterpreting the agent's decisions and planned actions. Despite previous research addressing human factors in autonomous shipping and remote control, few studies have focused on how to support the humans' mental processes in this new role. Therefore, this study performed a goal-directed task analysis addressing goals, decisions, and SA requirements for human-supervised collision avoidance. Data was obtained from in situ observations and interviews with nine navigators onboard passenger ferries, an appraisal of the collision regulations, and of relevant company documentation. The task analysis identified specific SA requirements to make agents, capable of collision and grounding avoidance, transparent to their users. The results further indicate a change towards increased cognitive activities required to verify agent performance. Therefore, providing insight into the agents' internal reasoning and actions becomes a key consideration in supporting future supervisors. Given the trends towards the application of artificially intelligent agents capable of autonomous behaviour, this study anticipates that transparency becomes an essential prerequisite for safe and effective human-autonomy system oversight. [ABSTRACT FROM AUTHOR]

Objective: Situation awareness has been identified as a key skill in maintaining safety in high-risk, dynamic industries. However, there is a lack of research evaluating situation awareness requirements and error types in agricultural operators. The aim of this study was to explore situation awareness among farmers in the United Kingdom (UK) when operating heavy agricultural machinery. Method: The study used an online qualitative survey to collect data in three main areas: situation awareness requirements, factors impacting situation awareness, and the safety context for UK farmers. A total of 57 farmers completed the survey, responding to seven open-ended questions. Data were analyzed using directed content analysis. Results: The results indicate the importance of situation awareness for safe and efficient work practice in farming. Situation awareness requirements span the machinery system, including awareness of internal cab systems and the status of implements attached to the external machine. Farmers needed to map and monitor the surrounding conditions in addition to considering personal requirements. Data also indicated the impact of a range of factors, including system-based elements such as blind spots, individual factors such as level of fatigue, and issues related to a lack of knowledge and failure to think ahead on the maintenance of situation awareness. Conclusion: This research highlights the situation awareness requirements for operating agricultural machinery in complex and dynamic environments. By taking a human factors approach, utilizing design and practical interventions, it may be possible to both support and enhance farmer situation awareness and, therefore, reduce errors and adverse incidents. [ABSTRACT FROM AUTHOR]

Highlights • Adults noted more targets, especially pedestrians and cyclists, compared to children. • Children focussed less on other road users, which were not as salient as cars. • Children missed more pre-specified targets and reacted to them more slowly than adults did. • Children seemed to have less situation awareness than adults. Abstract Cycling in urban environments requires the ability to distinguish between relevant and irrelevant targets quickly and reliably, so that potential hazards can be anticipated and avoided. In two experiments, we investigated where adults and children direct their attention when viewing videos filmed from a cyclist’s perspective. We wanted to see if there were any differences in the responses given by experienced adult cyclists, inexperienced adult cyclists, and child cyclists. In Experiment 1, 16 adults (19–33 years) were asked to watch ten videos and to point out things they would pay attention to by tapping a touchscreen (pointed out locations). Afterwards, they were asked to explain their answers. In Experiment 2, 17 adults (19–34 years) and 17 children (11–12 years) performed the same task with the same ten videos, but they were not asked to explain their answers afterwards. The data sets from these two experiments were pooled, creating three groups: ten experienced adult cyclists, 23 inexperienced adult cyclists and 17 children. A total of 23 clearly visible, traffic-relevant targets (pre-specified targets) had previously been identified in the videos. We investigated whether the participants’ pointed-out locations matched these targets (and if so, how fast they responded in pointing them out). We also investigated the number and vertical/horizontal dispersion of these pointed-out locations on the touchscreen. Adults pointed out more locations than children, especially pedestrians and cyclists. This result suggests that, while children focussed as well as adults on cars (arguably the most salient hazard), they were less able to identify other hazards (such as pedestrians or other cyclists). The children had also a larger vertical dispersion and a larger between-participant variation than the adults. Adults were faster at tapping the pre-specified targets and they missed them less often. Overall, the results suggest that 11–12 year old-cyclists have worse situation awareness in traffic than adults. [ABSTRACT FROM AUTHOR]

Situation awareness (SA) constitutes a critical factor in road safety, strongly related to accidents. This paper describes the evaluation of a proposed SA enhancement system (SAES) that exploits augmented reality through a head-up display (HUD). Two SAES designs were evaluation (information rich vs. minimal information) using a custom-made simulator and the Situation Awareness Global Assessment Technique with performance and EEG measures. The paper describes the process of assessing the SA of drivers using the SAES, through a series of experiments with participants in a Cave Automatic Virtual Environment. The effectiveness of the SAES was tested in a within-group research design. The results showed that the information rich (radar-style display) was superior to the minimal (arrow hazard indicator) design and that both SAES improved drivers’ SA and performance compared to the control (no HUD) design. Practitioner Summary: Even though driver situation awareness is considered as one of the leading causes of road accidents, little has been done to enhance it. The current study demonstrates the positive effect of a proposed situation awareness enhancement system on driver situation awareness, through an experiment using virtual prototyping in a simulator. [ABSTRACT FROM AUTHOR]

The military’s common operation picture (COP) is the concept where situation awareness is created before the eyes of high ranking commanders who gather remotely in a command and control headquarters to provide imperative advices and to make decision upon the emergency mission carried out by on-site soldiers. The underlying rationale is to integrate relevant technologies in order to enhance the situation awareness for disaster preparedness and quick response to emergency and communication blackout. The objective of the concept is to apply the COP created by combined geospatial and serious game for modelling military in-field operations during an incident of lacking communications. The paper explains the project initiated in the Defence Technology Institute that covers the plan to implement the integration of communications, military simulation and training, and unmanned vehicle technologies for the emerging situation awareness to be viewed from the COP. It will house current data and information of rescuer positions, images and live videos. In the commissioned vehicle, a dedicated map server is to host in-coming disparate data that has gone through digital image and video processing. For the COP display, Game Engine will play as a theatre that all data interacts in a common and easy-to-understand view. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: To propose a driver attention theory based on the notion of driving as a satisficing and partially self-paced task and, within this framework, present a definition for driver inattention.Background: Many definitions of driver inattention and distraction have been proposed, but they are difficult to operationalize, and they are either unreasonably strict and inflexible or suffer from hindsight bias.Method: Existing definitions of driver distraction are reviewed and their shortcomings identified. We then present the minimum required attention (MiRA) theory to overcome these shortcomings. Suggestions on how to operationalize MiRA are also presented.Results: MiRA describes which role the attention of the driver plays in the shared "situation awareness of the traffic system." A driver is considered attentive when sampling sufficient information to meet the demands of the system, namely, that he or she fulfills the preconditions to be able to form and maintain a good enough mental representation of the situation. A driver should only be considered inattentive when information sampling is not sufficient, regardless of whether the driver is concurrently executing an additional task or not.Conclusions: The MiRA theory builds on well-established driver attention theories. It goes beyond available driver distraction definitions by first defining what a driver needs to be attentive to, being free from hindsight bias, and allowing the driver to adapt to the current demands of the traffic situation through satisficing and self-pacing. MiRA has the potential to provide the stepping stone for unbiased and operationalizable inattention detection and classification. [ABSTRACT FROM AUTHOR]

Situation awareness (SA) is often argued to be a “sharp end” indicator of workplace safety, in the sense that inaccurate SA may be the proximal cause for operator error. However, traditional field or lab experiment measures of SA are difficult to combine with large-scale data collections to examine organizational influences on SA and the safety outcomes of SA. In the current study, offshore attendant vessel crew’s SA was measured with a self-report scale. Authentic leadership was modelled as a predictor, while self-report of committing unsafe actions at work and subjective risk assessment were modelled as outcome measures. Structural equation modelling showed the captain's leadership style to account for variation in SA and some variation in unsafe actions. Further, SA accounted for variation in unsafe actions and in subjective risk assessment. The study supports the assumption that SA has a crucial role in maritime safety. [ABSTRACT FROM AUTHOR]

• Situation awareness is important for carrying out nuclear power plant outage work. • Not comprehending situational information presents a main challenge in this context. • Insufficient work procedures are found to contribute to comprehension issues. • Not following (sufficient) work procedures contributes to errors in observing relevant situational information. In this study, we sought to identify if human errors responsible for incidents occurring during scheduled outage periods in nuclear power plants correspond to situation awareness errors in perception, comprehension, or projection. We also sought to identify factors contributing to situation awareness errors at all levels. To do this, we analysed 58 events occurring during planned nuclear power plant outages between 2016 and 2020, as documented in U.S. Licensee Event Reports (LERs). Of the human errors analysed in these events, 14 were classified as situation awareness errors related to perception (Level 1 errors), 30 were classified as situation awareness errors related to comprehension (Level 2 errors), and an additional 14 were classified as situation awareness errors related to projection (Level 3 errors). Furthermore, we found that insufficient procedure use was identified in the LERs as a factor contributing to most errors occurring at Level 1, whereas insufficient procedures was identified to contribute to most errors occurring at Level 2 and 3. [ABSTRACT FROM AUTHOR]

As unmanned aerial vehicles (UAVs) become widely used in various civil applications, many civil aerodromes are being transformed into a hybrid environment for both manned and unmanned aircraft. In order to make these hybrid aerodromes operate safely and efficiently, the autonomous taxiing system of UAVs that adapts to the dynamic environment has now become increasingly important, particularly under poor visibility conditions. In this paper, we develop a probabilistic self-learning approach for the situation awareness of UAVs' autonomous taxiing. First, the probabilistic representation for a dynamic navigation map and camera images are developed at the pixel level to capture the taxiway markings and the other objects of interest (e.g., logistic vehicles and other aircraft). Then, we develop a self-learning approach so that the navigation map can be maintained online by continuously map-updating with the obtained camera observations via Bayesian learning. An indoor experiment was undertaken to evaluate the developed self-learning method for improved situation awareness. It shows that the developed approach is capable of improving the robustness of obstacle detection via updating the navigation map dynamically. [ABSTRACT FROM PUBLISHER]

Complex socio-technical systems, such as road tunnels, can be designed and developed with more or less elements that can either positively or negatively affect the capability of their agents to recognise imminent threats or vulnerabilities that possibly lead to accidents. This capability is called risk Situation Awareness (SA) provision. Having as a motive the introduction of better tools for designing and developing systems that are self-aware of their vulnerabilities and react to prevent accidents and losses, this paper introduces the Risk Situation Awareness Provision (RiskSOAP) methodology to the field of road tunnel safety, as a means to measure this capability in this kind of systems. The main objective is to test the soundness and the applicability of RiskSOAP to infrastructure, which is advanced in terms of technology, human integration, and minimum number of safety requirements imposed by international bodies. RiskSOAP is applied to a specific road tunnel in Greece and the accompanying indicator is calculated twice, once for the tunnel design as defined by updated European safety standards and once for the ‘as-is’ tunnel composition, which complies with the necessary safety requirements, but calls for enhancing safety according to what EU and PIARC further suggest. The derived values indicate the extent to which each tunnel version is capable of comprehending its threats and vulnerabilities based on its elements. The former tunnel version seems to be more enhanced both in terms of it risk awareness capability and safety as well. Another interesting finding is that despite the advanced tunnel safety specifications, there is still room for enriching the safe design and maintenance of the road tunnel. [ABSTRACT FROM AUTHOR]

Mobile multi-machine environments consist of varying types of objects, either static or dynamic with the state known exactly or with some uncertainty. Sensors observe the environment from different positions and views, such as horizontally from the top of a mobile machine or vertically downward from an external observing machine. In this paper, we propose a simple grid-based framework for representing the information of varying types of objects in a 2-D environment and Bayesian methods for updating this information through observations and prediction models. This information about the current and near-future state of the environment is called situation awareness (SA). SA information can be utilized as the basis of the operator assistance system for enhancing the safety and efficiency of manual and semiautonomous multi-machine work environments. SA information can also be utilized in task planning of autonomous machines, via creating a dynamic costmap for path planning or entropy map for planning the optimal use of sensory systems. This paper aims at real-time mobile multi-machine environments; hence, the SA framework is kept simple for computational feasibility, but is also general enough to be applicable in other environments as well. Discussion on discretization errors and computational complexity are also covered. [ABSTRACT FROM PUBLISHER]

Mobile multimachine work environments, in general, consist of varying types of machines driving across a site to complete a moving or manipulation task. As the view from the machines over the environment can be limited due to the structure of the machines, the environment, and the moved/manipulated items, there is a risk of collision between machines. In this paper, we propose a situation awareness system aimed as a driver/operator assistive system to enhance the safety and efficiency of multimachine work environments. The system consists of the pose estimation of the machines, the M2M communication based on IEEE 802.11p, the future pose prediction of the machines, and a graphical user interface. The system is designed to be general enough to be applicable in diverse work environments, which is most easily implemented as a retrofit for existing machines. In this paper, the implementation of the system presented is a proof of concept, and the focus is on how the overall system works in a real harbor environment during operation, ultimately aiming for the collision avoidance of harbor machines. The field tests show promising results, particularly regarding the applicability of the M2M communication technology in a very challenging and uncertain harbor environment. [ABSTRACT FROM PUBLISHER]

This study examined accident reports ( n = 23) for collisions between attendant vessels and offshore facilities on the Norwegian continental shelf during the period of 2001–2011. An initial analysis indicated that the concept of situation awareness (SA) might be useful for providing a more detailed understanding of the processes that lead to collisions. SA is defined as ‘being aware of what is happening around you and understanding what that information means to you now and in the future’ (Endsley, 2012, p. 13). The first part of the study contains an analysis of accident reports that reveals that the collisions with offshore facilities were preceded by loss of SA on the bridge in 18 of the 23 instances. Three types of SA errors were identified: failure to perceive the situation correctly (Level 1 SA; n = 13), failure to comprehend the situation (Level 2 SA; n = 4), and failure to project the situation into the future (Level 3 SA; n = 1). In the second part of the study, the human, technological and organisational factors described in the accident reports are analysed to evaluate how the factors may have affected the duty officers‘ awareness of the situation. The results indicate that inadequate operation planning, inadequate bridge design, insufficient training, communication failures and distracting elements were the underlying factors that significantly contributed to the collisions. [ABSTRACT FROM AUTHOR]

This paper argues that state, system, and process descriptions of situation awareness (SA) are interdependent. Based on SA research from the last 30 years, the paper proposes a holistic SA framework. SA states emerge from processes of exploring situations through SA systems. Reflecting research on safety II (resilience), in describing SA states, the framework distinguishes frames (what situations are considered) from implications (regarding the situations) of objects on and of an event horizon. The paper describes and discusses SA system and process dependencies on SA states. It also describes SA system components as mediators and catalysts for SA, SA system properties (e.g. buffering SA), and dynamic SA system formation. Based on an analysis of four enactments of Air Traffic Control situations, the paper argues that what is domain-characteristic may not characterise all situations in a domain. The SA field could thus benefit from incrementally refining a nuanced cross-domain framework. [ABSTRACT FROM PUBLISHER]

This commentary is a response to Dekker's insightful article in this issue on situation awareness (SA). This is a concept that continues to excite strong debate but only because of the profound implications for the theoretical foundations and the effects that different approaches have for the work of human factors practitioners. We argue that Dekker's paper tacitly adopts one approach to SA, and in doing so will inevitably arrive at the point of questioning the concept in its entirety. If SA really is as deterministic and 'broken component' orientated as Dekker describes, then we would be in complete agreement, but instead we offer a counterpoint. We apply our distributed situation awareness approach to the key issues raised, answer all of Dekker's concerns, and offer a useful way forward. [ABSTRACT FROM AUTHOR]

• Limited situation awareness(SA) may cause accidents while operating a mobile plant. • Mobile plant operator's SA of other people in proximity is investigated. • Forklift operator's SA about other workers is affected by the complexity of the subtasks. • Control measures are proposed to prevent struck-by or caught in/between 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. [ABSTRACT FROM AUTHOR]