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.

PROGNOS: Predictive situational awareness with probabilistic ontologies

Abstract: Information in the battlefield comes from reports from diverse sources, in distinct syntax, and with different meanings. There are many kinds of uncertainty involved in this process, e.g., noise in sensors, incorrect, incomplete, or deceptive human intelligence, and others, which makes it essential to have a coherent, consistent, and principled means to represent such phenomena among the systems performing Predictive Situation Awareness (PSAW). PROGNOS is a PSAW system being developed to work within the operational context such as U.S. Navy's FORCENet. It employs probabilistic ontologies in a distributed system architecture as a means to provide semantic interoperability within an intrinsically complex and uncertain environment. This paper explores our current status in developing the system while addressing the major research challenges for making an effective PSAW system to support maritime operations.

Visual Analytics for Electromagnetic Situation Awareness in Radio Monitoring and Management

Abstract: Traditional radio monitoring and management largely depend on radio spectrum data analysis, which requires considerable domain experience and heavy cognition effort and frequently results in incorrect signal judgment and incomprehensive situation awareness. Faced with increasingly complicated electromagnetic environments, radio supervisors urgently need additional data sources and advanced analytical technologies to enhance their situation awareness ability. This paper introduces a visual analytics approach for electromagnetic situation awareness. Guided by a detailed scenario and requirement analysis, we first propose a signal clustering method to process radio signal data and a situation assessment model to obtain qualitative and quantitative descriptions of the electromagnetic situations. We then design a two-module interface with a set of visualization views and interactions to help radio supervisors perceive and understand the electromagnetic situations by a joint analysis of radio signal data and radio spectrum data. Evaluations on real-world data sets and an interview with actual users demonstrate the effectiveness of our prototype system. Finally, we discuss the limitations of the proposed approach and provide future work directions.

A taxonomy of autonomous vehicle handover situations

Abstract: This paper provides a taxonomy of different forms of autonomous vehicle handover situations. It covers scheduled, emergency and non-emergency handovers and it differentiates between system and driver initiated handovers. The purpose is to examine how the system and driver are responsible for different stages in the transition timeline, i.e., first alert, handover phase, and return to automated control (handback). This is examined from the perspective of SAE levels in comparison to aspects drawn from situational awareness. The work is complemented by analysis drawn from current practice within the insurance industry and interviews with insurers. The result is a closer examination of system and driver responsibility which is independent of but includes SAE levels with respect to specific handover situations. It also identifies gaps between the current legal liability for accidents when compared to aspects such as the situational awareness requirements placed on driver under different driving conditions.

Towards trustworthy automation: User interfaces that convey internal and external awareness

Abstract: Suppose we are given an autonomous vehicle that has limitations, meaning that it may need to transfer control back to the human driver to guarantee safety in certain situations. This paper presents work on designing a user interface to assist this hand off by considering the effects of the expression of internal and external awareness. Internal awareness is the concept of knowing whether or not the system is confident in its ability to handle the current situation. External awareness is the concept of being able to identify the limitations as the car is driving in terms of situational anomalies. We conduct a user study to examine what information should be presented to the driver, as well as the effects of expressing these levels of awareness on the driver's situational awareness and trust in the automation. We found that expressing uncertainty about the autonomous system (internal awareness) had an adverse effect on driver experience and performance. However, by effectively conveying the automation's external awareness on the anomaly, improvements were found in the driver's situational awareness, increased trust in the system, and performance after the transfer of control.