Aspects Of Situation Awareness Research Articles

A Survey on Cyber Situation-awareness Systems: Framework, Techniques, and Insights

Cyberspace is full of uncertainty in terms of advanced and sophisticated cyber threats that are equipped with novel approaches to learn the system and propagate themselves, such as AI-powered threats. To debilitate these types of threats, a modern and intelligent Cyber Situation Awareness (SA) system needs to be developed that has the ability of monitoring and capturing various types of threats, analyzing, and devising a plan to avoid further attacks. This article provides a comprehensive study on the current state-of-the-art in the cyber SA to discuss the following aspects of SA: key design principles, framework, classifications, data collection, analysis of the techniques, and evaluation methods. Last, we highlight misconceptions, insights, and limitations of this study and suggest some future work directions to address the limitations.

Human Factor Aspects of Situation Awareness in Autonomous Cars – An Overview of Psychological Approaches

Human Factor Aspects of Situation Awareness in Autonomous Cars – An Overview of Psychological Approaches

Situational awareness during a full-scale exercise in an underground mine: A qualitative single-case study of the ambulance incident commander

IntroductionUnderground environments present challenges for providing and managing effective emergency care. Situational awareness (SA) has been suggested as a critical process to the management of care. AimThis study aims to explore the process of SA in the tasks of an ambulance incident commander (AIC) during a fullscale underground mine exercise. MethodsData consisted of video recordings, audiotapes and fieldnotes; these were subjected to content analysis based on the categories from the Busby Theory of Situational Awareness in Multi-casualty Incidents. ResultsThe results show that the underground mining environment presented the AIC with specific challenges for the SA process with respect to aspects such as situational information about the scene and the victims, as well as with making decisions for ambulance personnel so they could perform their work safely, and having a structured manner to counteract information overload. Both technical and non-technical aspects influenced the process. ConclusionThe AIC’s situational awareness was largely built through coordinated communications and actions with collaborating actors. The results of this study can be used for further exploration of how to train and support people in medical leadership roles on aspects of SA in emergency care, as well as on how to evaluate educational outcomes through exercises.

Assessing the Effect of Countdown Featured TOR Signal on Drivers in Automated Driving Mode Change

In conditional automated driving, drivers may be required starting manual driving from automated driving mode after take-over request (TOR). The objective of the study was to investigate different TOR features for drivers to engage in manual driving effectively in terms of reaction time, preference, and situation awareness (SA). Five TOR features, including four features using countdown, were designed and evaluated, consisted of combinations of different modalities and codes. Results revealed the use of non-verbal sound cue (beep) yielded shorter reaction time while participants preferred verbal sound cue (speech). Drivers' SA was not different for TOR features, but the level of SA was affected by different aspects of SA. The results may provide insights into designing multimodal TOR along with drivers' behavior during take-over tasks.

A multidimensional framework to study situation awareness in u-learning systems

This research is devoted to the study of the situation awareness from ubiquitous learning (u-learning) systems’ perspective. Related researches identified literature provide different visions and sometimes conflicting ones to the concept of situation awareness. Given this misunderstanding, this paper aims to bring a common and organized characterisation of this concept for the u-learning field. A multidimensional framework dedicated for situation-aware u-learning systems is then defined. This framework is composed of four different and complementary worlds. Each world helps to understand, analyse and describe in-depth a particular aspect of situation awareness in u-learning systems. The paper presents a structured description of the framework’s worlds. An evaluation of the research works identified in literature based on the framework’s worlds is then presented. The provided assessment helps identifying problems involving situation awareness in u-learning systems which could be a starting point for possible future research opportunities.

Situation awareness in the speech therapy domain: A systematic mapping study

Situation Awareness (SA) involves the correct interpretation of a situation, allowing a system to respond to the observed environment and providing support for decision making in many systems domains. Speech therapy is an example of domain where situation awareness can provide benefits, since practitioners should monitor the patient in order to perform therapeutic actions. However, there are a few studies in the area that address reasoning about a situation to improve these tasks. For this reason, this systematic mapping study aims to identify and compare different proposals in the speech therapy domain in order to verify which aspects related to obtaining and maintaining SA are supported. Our analyzes provide useful insights on whats aspects of SA are best integrated in the speech domain - such as knowledge bases and adaptation - and other aspects that remain to be improved - like the action support and projection abilities. Also, this paper includes statistics, methodologies used by different authors and other issues involving research processes. As main contributions, this work presents an overview of the SA integration in the speech therapy domain, discussing challenges in the area and providing directions for further research.

Decision making support in security forces command centers at open air music festivals: Localization of resources and sharing information

Abstract We describe a case study on decision making in command centers of security forces at major open air music festivals. Our goal was to assess current modus operandi and to identify design implications. We have carried out two expert interviews, two field observations and four group discussions with experts based on a fully functional prototype as IT artifact to concretize discussions. Key insights are that in this case localization of relevant resources is the most important aspect of situation awareness, and that state of current knowledge needs to be clearly shared within the command center.

A Review of Situation Awareness Assessment Approaches in Aviation Environments

Situation awareness (SA) is an important constituent in human information processing and essential in pilots' decision-making processes. Acquiring and maintaining appropriate levels of SA is critical in aviation environments as it affects all decisions and actions taking place in flights and air traffic control. This paper provides an overview of recent measurement models and approaches to establishing and enhancing SA in aviation environments. Many aspects of SA are examined including the classification of SA techniques into six categories, and different theoretical SA models from individual, to shared or team, and to distributed or system levels. Quantitative and qualitative perspectives pertaining to SA methods and issues of SA for unmanned vehicles are also addressed. Furthermore, future research directions regarding SA assessment approaches are raised to deal with shortcomings of the existing state-of-the-art methods in the literature.

Various aspects of situation awareness with respect to human-machine-interaction while using optoavionic cockpit instrumentation in aircraft

Various aspects of situation awareness with respect to human-machine-interaction while using optoavionic cockpit instrumentation in aircraft

Quantitative Analysis of Situation Awareness (QASA): modelling and measuring situation awareness using signal detection theory

This paper presents a model of situation awareness (SA) that emphasises that SA is necessarily built using a subset of available information. A technique (Quantitative Analysis of Situation Awareness – QASA), based around signal detection theory, has been developed from this model that provides separate measures of actual SA (ASA) and perceived SA (PSA), together with a feature unique to QASA, a measure of bias (information acceptance). These measures allow the exploration of the relationship between actual SA, perceived SA and information acceptance. QASA can also be used for the measurement of dynamic ASA, PSA and bias. Example studies are presented and full details of the implementation of the QASA technique are provided.Practitioner Summary: This paper presents a new model of situation awareness (SA) together with an associated tool (Quantitative Analysis of Situation Awareness – QASA) that employs signal detection theory to measure several aspects of SA, including actual and perceived SA and information acceptance. Full details are given of the implementation of the tool.

Towards artificial situation awareness by autonomous vehicles

This paper presents a novel approach to artificial situation awareness for an autonomous vehicle operating in complex dynamic environments populated by other agents. A key aspect of situation awareness is the use of mental models to predict future states of the environment, allowing safe and rational routing decisions to be made. We present a technique for predicting future discrete state transitions (such as the commencement of a turn) by other agents, based upon an uncertain mental model. Predictions take the form of univariate Gaussian Probability Density Functions which capture the inherent uncertainty in transition time whilst still providing great benefit to a decision making system. The prediction distributions are compared with Monte Carlo simulations and show an excellent correlation over long prediction horizons.

CoJACK: A high-level cognitive architecture with demonstrations of moderators, variability, and implications for situation awareness

Abstract We report a high-level architecture, CoJACK, that provides insights on behavior variability, situation awareness, and behavioral moderators. CoJACK combines Beliefs/Desires/Intentions (BDI) agents’ high-level knowledge representation and usability with several aspects of low-level cognitive architectures, including processing time predictions, errors, and traceability. CoJACK explores new areas for cognitive architectures, such as variability arising from moderators. It also allows aspects of situation awareness (SA) in a cognitive architecture to be explored. Its behavior and the effects of moderators on behavior are demonstrated in a simple adversarial environment. It provides lessons for other architectures including how to define, measure, and control variability due to individual and temporal aspects of cognition; the importance of SA and knowledge representations necessary to support complex SA; the potential for parameter sweeps and paths as measures of variability; and some of the complexities that will arise when aspects of moderators and SA are added to cognitive architectures.

Easy rider meets knight rider: an on-road exploratory study of situation awareness in car drivers and motorcyclists

A comparison of two very different vehicle designs, cars and motorcycles, allows the effect of vehicle feedback on driver/rider Situation Awareness (SA) to be analysed in an ecologically valid on-road setting. The findings justify this comparison and reveal that the structure, quantity and type of SA is different for car drivers compared to motorcyclists. In addition, the differences in the structure of SA are suggestive of some behavioural incompatibility in which certain aspects of SA may be appropriate to car driving but not motorcycling. An analysis of effect sizes within this exploratory study is suggestive of further areas for targeted research.

선박조종시뮬레이터를 이용한 반복 항해 훈련이 선박 조종에 미치는 영향

본 연구는 선박 조종에 영향을 주는 대표적 요인들(충돌위험 정도, 목표선박의 항로변경 여부 및 주변 선박 수)을 체계적으로 조작한 조건들에서 항해사의 상황인식 훈련이 항해사의 선박 조종 능력에 어떠한 차이를 가져오는지 선박조종시뮬레이터를 이용하여 분석하였다. 본 연구 결과를 요약하면 다음과 같다. 첫째, 항해와 관련된 상황인식 훈련을 받은 조건에서 실험참가자들은 여러 선박 조종 요소들(목표선박과의 거리 유지와 충돌 비율)에서 훈련을 받지 않은 조건에 비해 수행이 우수하였다. 둘째, 훈련을 받지 않은 실험참가자들은 목표선박이 평시상황에서 항로를 변경하는 경우 선박 조종에 가장 큰 어려움을 겪었으나 훈련 이후에는 이러한 경향이 크게 감소하여 동일한 조건에서 수행이 향상되는 것이 관찰되었다. 이러한 결과들을 종합하면, 선박 조종에서의 상황인식에 대한 여러 요소들의 훈련은 항해사들의 기본적 선박 조종능력에서 우수한 수행을 이끌 수 있는 것으로 판단된다. The purpose of the present study was to investigate the effect of mariner's situation awareness(SA) training on navigation performance using a full mission ship-handling simulator. For this purpose, the mariners were trained in terms of various aspects of SA. Independent variables such as risk levels of ship-to-ship collision, navigational route types of 'target ship(TS)', and number of ships around the own ship(OS) were systematically varied, and dependent variables of closest point of approach(CPA) between TS and OS, number of collision, types of collision-avoidance strategy were measured The results can be summarized as followings. First, training on mariner's SA appeared to induce improved performances in various aspects of ship handling. Second, mariners in the routine navigation situation where TS had priority following maritime rules seemed to suffer to prepare collision avoidance when the TS altered its route. However, this tendency greatly reduced after the training These results suggest the benefit of mariner's SA training on maritime safety.

Effects of Verbal and Spatial-Imagery Tasks on Drivers' Situation Awareness of Traffic Information

Safe driving requires the driver to maintain situation awareness of dynamic traffic information, including surrounding vehicles' spatial information and other properties. Previous research has shown that performing mental secondary tasks drastically changes drivers' visual scanning behaviors (Recarte & Nunes, 2000). But it remains unclear whether the modified visual scanning pattern results in deterioration in drivers' situation awareness of surrounding traffic. More specifically whether different aspects of drivers' situation awareness would be affected by secondary tasks differently, or whether different types of secondary task would interact with the different aspects of the situation awareness. This study employed a change detection paradigm (Zheng, McConkie, & Tai, 2003) to investigate these questions in a simulated dynamic driving environment. The results showed the general negative effect of secondary tasks on the driver's situation awareness, with the spatial-imagery task producing greater interference than the verbal task. Moreover, both secondary tasks interfere more with the detection of the vehicle location displacements than with the detection of the vehicle color or identity changes.

Model for Situation Awareness and Driving: Application to Analysis and Research for Intelligent Transportation Systems

The concept of situation awareness (SA)—applied broadly over the last decade to human factors issues in aviation, nuclear power generation, and military combat systems—has only recently been introduced to the analysis of driver behavior. In a driving context, SA involves spatial, temporal, goal, and system awareness. These aspects of SA have been integrated into a goal-oriented model of driver behavior that encompasses strategic, tactical, and operational goals of driving. Maintenance of appropriate SA for each type of goal is based on three underlying processes: perception, comprehension of disparate information, and projection and prediction. The model can be used as a basis for understanding the possible impact of new generations of intelligent transportation systems (ITSs) on driver performance. The model allows ITSs to be analyzed for how they are likely to enhance or impair a driver’s performance in pursuit of each type of driving goal. The model may provide a way to determine how an ITS supports or interferes with the required SA to meet a driving goal (e.g., an onboard navigation system that assists strategic decisions).

A Methodology for Measuring the Judgmental Components of Situation Awareness

Situation awareness (SA) research has highlighted many important problems concerning the ability of operators to cope with opaque interfaces in complex systems. This same research, however, has shown that SA can be extremely difficult to measure. We therefore provide a methodology for measuring one functional aspect of SA: the operator's ability to judge the state of the task environment on the basis of uncertain information. The approach is based on Judgment Analysis and Brunswik's lens model and its modern extensions.

Human Factors Issues in Advanced Moving-map Systems

Vector-based maps are an advanced capability of digital moving-map systems that are easily customised and can be powerful aids to aircrew information processing and decision-making. However, they may place excessive demands on an aircrew's information processing requirements, cause an increase in workload, and degrade situational awareness if the user interface is not designed properly. There is little information available about the human factors and situational awareness issues relevant to vector-based maps. In this paper, we summarise relevant research on human factors and situational awareness aspects of using vector-based maps, identify key issues, and recommend directions for future research.

Broadening the Measurement of Situation Awareness through Cognitive Engineering Methods

Situation awareness (SA) and team SA are popular concepts, yet vaguely defined and inadequately measured. They involve representations of the current situation, performance resulting from those representations, and cognitive structures and processes leading to those representations. Current measures of individual and team SA focus on the assessment of performance or the accuracy of the resulting situation model at the expense of other aspects of SA, such as situation assessment, mental models, and team process behaviors. As a result, these measures fail to capture the richness of the constructs of individual and team SA, critical for applications involving training and team SA. We propose that a cognitive engineering approach to measuring SA which focuses on the elicitation of the cognition underlying SA, can extend measurement by overcoming many of the current limits. As an illustration, the measurement of situation models using this approach is presented.

Relationship between scene complexity and perceptual performance for computer graphics simulations

An important goal for the design of visual displays is to determine how much realism or scene complexity to include in a computer simulation to reach a given level of performance. This is an important task since the present trend in computer graphics is to include the highest level of realism or scene complexity possible in a simulation. However, it may not be necessary to always include the highest level of realism or complexity to reach an acceptable level of performance. In fact, needless degrees of realism, and thus computational resources, may be wasted in the quest for ‘photographic’ realism. To study the relationship between scene complexity and human performance, three different simulations of scene complexity were modeled for a final approach task. The subject's task were to estimate two aspects of situation awareness, perceived altitude and aimpoint, during a simulated final approach at nine unique distances to threshold. The three levels of scene complexity included a homogeneous Lambertian shaded flat surface, farmlands, and farmlands with hills. The results indicated that increasing the level of scene complexity lead to better performance in judging both altitude and aimpoint during the simulated final approach. The relationship between scene complexity and perceptual performance for computer graphics simulations are discussed.