Situation awareness

About: Situation awareness is a research topic. Over the lifetime, 7380 publications have been published within this topic receiving 108695 citations. The topic is also known as: SA & situational awareness.

Leading article: What can we do to improve individual and team situational awareness to benefit patient safety?

Abstract: It is increasingly being recognised that human factors can contribute to error in complex safety systems. Healthcare, however, has a long way to go before the promotion of training in, and awareness of, human factors will catch up with other high-risk organisations. A critical component that is deemed essential both for improving clinical performance and reducing medical error is situational awareness (SA). This is dynamic and can reduce quickly or be lost entirely, particularly when the workload is heavy. Tunnel vision, in which healthcare professionals concentrate on a single aspect of a patient's care, is just one example of reduced awareness that can be detrimental to safety. As in aviation and other high-risk organisations, a reduction in SA, if not recognised by individuals or the wider team, can lead to serious or potentially fatal outcomes. We therefore give an overview of SA and show how it can easily be reduced. We also suggest some simple but effective ways to improve it and in turn improve patient safety. We emphasise the importance of clinical teams looking out for each other, particularly in the operating theatre.

Expanded field of view (EFOV) display for real-time, manned, interactive air combat simulation, including close-in combat

Abstract: An expanded field of view visual display concept capable of conducting credible close-in or within visual range (WVR) air-to-air combat from a single computer graphics display screen. By use of the invention, the visual scene content that normally exists outside and around the cockpit of a fighter aircraft can be condensed onto a single CRT screen or video projection screen in such a manner that pilots have good situational awareness, even in close-in-combat, and can fly credible air combat. An expanded field of view visual display is created, referred to as target coordinate display (TCD), capable of conducting credible close-in simulated air combat from a single CRT display or video projection screen. The display handles multiple aircraft, shows friendly aircraft formations, is usable in real time, shows weapon release information, is easily adapted to by pilots, and yields credible air combat simulation results.

Strategic Workload and the Cognitive Management of Advanced Multi-Task Systems

Abstract: : Improved technology and automation are being advocated as the solution to problems of lagging productivity and human error However, the very technology that is sought to improve productivity and reduce human crewmember's workload often has the opposite effect An alternative is human-centered automation that aids and supports the human crewmember To design it requires an expanded view of workload as a strategic task management problem, contrasted with the more traditional view of workload as competition for a limited pool of processing resources at any one time We introduce a theoretical framework for understanding human cognitive processing that builds on active theories of perception, connectionist theories of associative knowledge structures, and schema theories of comprehension The framework addresses mechanisms of attention, situation awareness, and real-time management of multiple streams of activity

A granular computing framework for approximate reasoning in situation awareness

Abstract: We present our results on the adoption of a set-theoretic framework for granular computing to situation awareness. The proposed framework guarantees a high degree of flexibility in the process of creation of granules and granular structures allowing to satisfy the wide variety of requirements for perception and comprehension of situations where some elements must be perceived per similarity, others per spatial proximity, some must be fused to improve their comprehension, and so on. A second value is the support for approximate reasoning in situation awareness. A granular structure in particular represents a snapshot of a situation, and is a building block for the development of tools and techniques to reason on situation in order to reduce situation awareness errors and accelerate the process of decision-making. To this purpose, we show a technique to support operators in the analysis of conformity between a recognized situation and an expected one. A third value is the fact that we can support operators in having rapid and indicative measures of how two situations, e.g. a recognized and a projected, may differ. A preliminary evaluation instantiating our approach with self-organizing maps is reported and discussed. The results are encouraging with respect to the capability of improving perception and comprehension of a situation, reducing comprehension errors and supporting projection of situations.

Mining maritime traffic conflict trajectories from a massive AIS data

Abstract: The growing volume of maritime traffic is proving a hindrance to navigational safety. Researchers have sought to improve the safety of maritime transportation by conducting statistical analysis on historical collision data in order to identify the causes of maritime collisions. However, this approach is hindered by the limited number of incidents that can be collected in a given area over a given period of time. Automatic Identification System (AIS) has made available enormous quantities of maritime traffic data. Trajectory data are collected through the electronic exchange of navigational data among ships and terrestrial and satellite base stations. Due to a massive AIS data of recording ship movement, such data provide great opportunity to discover maritime traffic knowledge of movement behavior analysis, route estimation, and the detection of anomalous behaviors. Our objective in this paper was to identify potential between-ship traffic conflicts through the discovery of AIS data. Traffic conflict refers to trajectories that could lead to a collision if the ships do not take any evasive action. In other words, conflicting trajectories can be treated as a near-collision cases for analysis. The prevention of collisions requires an efficient method by which to extract conflicting trajectories from a massive collection of AIS data. To this end, we developed a framework CCT Discovery that allows the automated identification of clusters of conflicting trajectories (CCTs) from AIS data without supervision. Experiments based on real-world data demonstrate the efficacy of the proposed framework in terms of accuracy and efficiency. For improvement in the navigational traffic safety, the discovered data of conflict trajectory can contribute to numerous applications, such as collision situation awareness and prediction, anti-collision behaviors modeling and recommendation, and conflict area analysis for maritime traffic flow management.