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.

Team situation awareness for process control safety and performance

Abstract: This paper defines situation awareness (SA) and discusses its importance to operator-machine system safety and functioning in the context of process control activities. Specifically, identified are relationships of human detection of critical process cues converying the status of automated control systems and operator interpretation of the meaning and relevance of such information to the potential for negative incidents in chemical processing. Beyond individual operator SA in interacting with control systems, intra- and inter- work team SA are discussed for supporting individual attainment of process control responsibilities. Factors critical to team SA are discussed. “Road blocks” to team SA are also analytically examined. Lastly, methods for assessing individual and team SA are reviewed and vehicles for relating outcomes of these methods to changes in process control operator and team behavior to improve human-machine system safety and performance are relayed.

Editorial: BeAware!-Situation awareness, the ontology-driven way

Abstract: Information overload is a severe problem for human operators of large-scale control systems as, for example, encountered in the domain of road traffic management. Operators of such systems are at risk to lack situation awareness, because existing systems focus on the mere presentation of the available information on graphical user interfaces-thus endangering the timely and correct identification, resolution, and prevention of critical situations. In recent years, ontology-based approaches to situation awareness featuring a semantically richer knowledge model have emerged. However, current approaches are either highly domain-specific or have, in case they are domain-independent, shortcomings regarding their reusability. In this paper, we present our experience gained from the development of BeAware!, a framework for ontology-driven information systems aiming at increasing an operator's situation awareness. In contrast to existing domain-independent approaches, BeAware!'s ontology introduces the concept of spatio-temporal primitive relations between observed real-world objects thereby improving the reusability of the framework. To show its applicability, a prototype of BeAware! has been implemented in the domain of road traffic management. An overview of this prototype and lessons learned for the development of ontology-driven information systems complete our contribution.

Distribution of Attention, Situation Awareness and Workload in a Passive Air Traffic Control Task: Implications for Operational Errors and Automation

Abstract: A study was conducted to investigate factors underlying operational errors (OEs) in en route air traffic control (ATC). Twenty active-duty controllers watched recreations of OEs and were asked to r...

Staged-learning process and system for situational awareness training using integrated media

Abstract: A method and system is disclosed for a staged learning process for situational awareness training using integrated media wherein a mix of classroom lectures, computer-based training and immersive simulation is used to advance the student from an operational stage to a tactical stage to a strategic stage. During the simulation exercises, the student is presented with a realistic interactive driving environment and external stimuli. The simulator measures and records the student's performance, generating a score based on various factors. The student is then able to review his or her performance or parts thereof from multiple perspectives. The process teaches, tests and reinforces situational awareness in drivers through an orderly, consistent “preview, drive, review” procedure and gives the student a level of situational awareness generally achieved by a driver with greater experience.

Research on Road Traffic Situation Awareness System Based on Image Big Data

Abstract: Road traffic is an important component of the national economy and social life. Promoting intelligent and Informa ionization construction in the field of road traffic is conducive to the construction of smart cities and the formulation of macro strategies and construction plans for urban traffic development. Aiming at the shortcomings of the current road traffic system, this article, on the basis of combining convolution neural network, situational awareness technology, database and other technologies, takes the road traffic situational awareness system as the research object, and analyzes the information collection, processing, and analysis process of road traffic situational awareness system. Convolutional neural networks (CNN), region-CNN (R-CNN), fast R-CNN, and faster R-CNN are used for vehicle class classification and location identification in road image big data. The deep convolutional neural network model based on road traffic image big data was further established, and the system requirements analysis and system framework design and implementation were carried out. Through the analysis and trial of actual cases, the results show the application effect of the realized road traffic situational awareness system, which provides a scientific reference and basis for the establishment of modern intelligent transportation system.