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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.


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Patent
Rolf Stefani1
29 Dec 2005
TL;DR: In this paper, a lightweight autonomous device is provided that can determine its own positional information, detect, via sensors with which it communicates, a position of a moving or stationary target, calculate a relative position of that target to the device's own known position, and transmit data regarding the target to a local or remote receiving station where the data can be interpreted and displayed.
Abstract: A lightweight autonomous device is provided that can (1) determine its own positional information, (2) detect, via sensors with which it communicates, a position of a moving or stationary target, (3) calculate a relative position of that target to the device's own known position, and (4) transmit data regarding the target to a local or remote receiving station where the data can be interpreted and displayed. The disclosed device may employ global positioning satellites for position-keeping, detect and collect information from individual sensors regarding targets, calculate position information regarding targets by comparing sensor information with the device's known position, and communicate information to a compatible receiving system at a remote location, as well as performing local processing on the information. The receiving system may display the information to provide a situational awareness overview to a user to coordinate or control personnel activities and/or vehicular movements based on the displayed information.

28 citations

Proceedings ArticleDOI
02 May 2017
TL;DR: The findings indicate that overall, drivers' performance and situation awareness improved when using this 3D auditory advisory traffic information system (3DAATIS), and the results also point towards the advantages and limitations of the use of advisory 3D-sounds in cars.
Abstract: Within vehicle Human Machine Interface design, visual displays are predominant, taking up more and more of the visual channel for each new system added to the car, e.g. navigation systems, blind spot information and forward collision warnings. Sounds however, are mainly used to alert or warn drivers together with visual information. In this study we investigated the design of auditory displays for advisory information, by designing a 3D auditory advisory traffic information system (3DAATIS) which was evaluated in a drive simulator study with 30 participants. Our findings indicate that overall, drivers' performance and situation awareness improved when using this system. But, more importantly, the results also point towards the advantages and limitations of the use of advisory 3D-sounds in cars, e.g. attention capture vs. limited auditory resolution. These findings are discussed and expressed as design implications.

28 citations

Proceedings ArticleDOI
01 Jun 2017
TL;DR: A modular framework for traffic regulations based decision-making of automated vehicles that builds on a semantic traffic scene representation formulated as ontology and includes knowledge about traffic regulations.
Abstract: This paper presents a modular framework for traffic regulations based decision-making of automated vehicles. It builds on a semantic traffic scene representation formulated as ontology and includes knowledge about traffic regulations. The semantic representation supports traffic situation classification by reasoning, providing improved situational awareness for the automated vehicle. Decision-making rules are directly derived from traffic regulations and concepts used in the ontology are harmonized with concepts used in traffic regulations. Due to the modular structure of the developed ontology, switching between different sets of national traffic regulations becomes a simple process. The methodology is evaluated for a variety of traffic scenarios, building up from basic to complex urban scenarios containing intersections, traffic regulating police officers and crossing street railways.

28 citations

Journal ArticleDOI
TL;DR: The article ends with a discussion of how the situated SA approach can be used to explain the acquisition of shared SA in distributed teams and to guide applied research relating to the evaluation and development of NextGen concepts and tools.
Abstract: The Next Generation Air Transportation System (NextGen) is expected to revolutionize how air traffic will be managed and significantly enhance the capacity of the National Airspace System in the United States. Because NextGen is a system that requires a high level of interaction between human operators and technology, there is a need to assess how NextGen tools and concepts of operation will impact operator situation awareness (SA). The goal of this study is to highlight the importance of SA to operator performance in complex systems. The defended view is that SA is situated, which means that operators rely in fundamental ways on interactions with external tools to maintain their understanding of a situation, minimizing internal memory storage of task relevant information. Consequently, SA metrics must be conducted in the context where operators have access to their displays and tools. The article ends with a discussion of how the situated SA approach can be used to explain the acquisition of shared SA in...

28 citations

Journal ArticleDOI
TL;DR: A novel interactive learning framework to improve the classification process in which the user iteratively corrects the relevancy of tweets in real-time to train the classification model on-the-fly for immediate predictive improvements.
Abstract: Various domain users are increasingly leveraging real-time social media data to gain rapid situational awareness. However, due to the high noise in the deluge of data, effectively determining semantically relevant information can be difficult, further complicated by the changing definition of relevancy by each end user for different events. The majority of existing methods for short text relevance classification fail to incorporate users' knowledge into the classification process. Existing methods that incorporate interactive user feedback focus on historical datasets. Therefore, classifiers cannot be interactively retrained for specific events or user-dependent needs in real-time. This limits real-time situational awareness, as streaming data that is incorrectly classified cannot be corrected immediately, permitting the possibility for important incoming data to be incorrectly classified as well. We present a novel interactive learning framework to improve the classification process in which the user iteratively corrects the relevancy of tweets in real-time to train the classification model on-the-fly for immediate predictive improvements. We computationally evaluate our classification model adapted to learn at interactive rates. Our results show that our approach outperforms state-of-the-art machine learning models. In addition, we integrate our framework with the extended Social Media Analytics and Reporting Toolkit (SMART) 2.0 system, allowing the use of our interactive learning framework within a visual analytics system tailored for real-time situational awareness. To demonstrate our framework's effectiveness, we provide domain expert feedback from first responders who used the extended SMART 2.0 system.

28 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023429
2022949
2021302
2020417
2019422