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.

Overview of Cyber Situation Awareness

Abstract: Improving a decision maker’s1 situational awareness of the cyber domain isn’t greatly different than enabling situation awareness in more traditional domains2 Situation awareness necessitates working with processes capable of identifying domain specific activities as well as processes capable of identifying activities that cross domains These processes depend on the context of the environment, the domains, and the goals and interests of the decision maker but they can be defined to support any domain This chapter will define situation awareness in its broadest sense, describe our situation awareness reference and process models, describe some of the applicable processes, and identify a set of metrics usable for measuring the performance of a capability supporting situation awareness These techniques are independent of domain but this chapter will also describe how they apply to the cyber domain

MmWave Vehicular Beam Selection With Situational Awareness Using Machine Learning

Abstract: Establishing and tracking beams in millimeter-wave (mmWave) vehicular communication is a challenging task. Large antenna arrays and narrow beams introduce significant system overhead configuring the beams using exhaustive beam search. In this paper, we propose to learn the optimal beam pair index by exploiting the locations and types of the receiver vehicle and its neighboring vehicles (situational awareness), leveraging machine learning classification and past beam training data. We formulate the mmWave beam selection as a multi-class classification problem based on hand-crafted features that capture the situational awareness in different coordinates. We then provide a comprehensive comparison of the different classification models and various levels of situational awareness. Furthermore, we examine several practical issues in the implementation: localization is susceptible to inaccuracy; situational awareness at the base station (BS) can be outdated due to vehicle mobility and limited location reporting frequencies; the situational awareness may be incomplete since vehicles could be invisible to the BS if they are not connected. To demonstrate the scalability of the proposed beam selection solution in the large antenna array regime, we propose two solutions to recommend multiple beams and exploit an extra phase of beam sweeping among the recommended beams. The numerical results show that situational awareness-assisted beam selection using machine learning is able to provide beam prediction, with accuracy that increases with more complete knowledge of the environment.

Workload or Situational Awareness?: TLX vs. SART for Aerospace Systems Design Evaluation

Abstract: Both workload and situational awareness (SA) have been recognised as important considerations in aerospace system design evaluation. This paper considers the use of subjective techniques for the me...

Augmented reality-based system and method to show the location of personnel and sensors inside occluded structures and provide increased situation awareness

Abstract: An augmented reality system provides enhanced situational information to personnel located within an environment. A tracking system obtains viewpoint information corresponding to a real-time view of said environment. A processing system receives information from one or more sensors. Information includes sensor location information and status information about the environment and personnel therein. The processing system generates graphics using the sensor location information and the viewpoint information. Graphics include visual representations of said status information. A display displays the generated graphics on a display at a supervisor station that is outside of said environment such that graphics are superimposed on the real-time view.

Brain–Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems

Abstract: Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.