Topic
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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TL;DR: This paper introduces meta-modeling concepts that allow us to assess and project situations and actions using semantic web technology and compares the runtime performance of the situation comprehension capabilities of a generic, ontology-driven implementation and a domain-specific relational-database-backed implementation.
27 citations
18 Jun 2012
TL;DR: The proposed approach is to design the system in a top-down manner, by identifying system metrics such as approximate measures of awareness, and then characterizing component models and their interactions, and to derive an overall awareness quality metric.
Abstract: The concept of cooperative vehicle safety (CVS) is based on cooperation of vehicles in achieving real-time situation awareness for the purpose of safer (and possibly autonomous) driving. Since CVS is a safety system, situation awareness has to be real-time with high accuracy. Cooperation in the context of CVS is achieved through vehicular networks that are tuned to the purpose of vehicle state tracking in a neighborhood around each vehicle. In this paper, we describe different methodologies in approaching the design of CVS, and propose a systematic Cyber-Physical Systems approach to the design of CVS. Our proposed approach is to design the system in a top-down manner, by identifying system metrics such as approximate measures of awareness, and then characterizing component models and their interactions. For this purpose, processes that handle vehicle state estimation and dissemination of state information are studied and their interactions are modeled in order to derive an overall awareness quality metric. The result of analyzing and modeling such effects is then used in studying the design of adaptive control schemes for each component of CVS.
27 citations
27 Apr 2007
TL;DR: The approach taken at TNO is discussed in the design and assessment of system concepts for future IRST and EO system concepts including signal processing, to improve system performance.
Abstract: In recent years, operations executed by naval forces have taken place at many different locations. At present, operations against international terrorism and asymmetric warfare in coastal environments are of major concern. In these scenarios, the threat caused by pirates on-board of small surface targets, such as jetskis and fast inshore attack crafts, is increasing. In the littoral environment, the understanding of its complexity and the efficient use of the limited reaction time, are essential for successful operations. Present-day electro-optical sensor suites, also incorporating Infrared Search and Track systems, can be used for varying tasks as detection, classification and identification. By means of passive electrooptical systems, infrared and visible light sensors, improved situational awareness can be achieved. For long range capability, elevated sensor masts and flying platforms are ideally suited for the surveillance task and improve situational awareness. A primary issue is how to incorporate new electro-optical technology and signal processing into the new sensor concepts, to improve system performance. It is essential to derive accurate information from the high spatial resolution imagery created by the EO sensors. As electro-optical sensors do not have all-weather capability, the performance degradation in adverse scenarios must be understood, in order to support the operational use of adaptive sensor management techniques. In this paper we discuss the approach taken at TNO in the design and assessment of system concepts for future IRST development. An overview of our maritime programme in future IRST and EO system concepts including signal processing is presented.
27 citations
TL;DR: Assessments of cross-task cue utilisation may be used to distinguish the propensity for prospective trainees to acquire the situational awareness necessary for complex, process control tasks such as air traffic control.
27 citations
17 Dec 2007
TL;DR: ASAP shows that it scales up to a thousand of sensor nodes, significantly mitigates infrastructure and cognitive overload, and reduces false negatives and false positives due to its ability to integrate multi-modal sensing.
Abstract: Situation awareness is an important application category in cyber-physical systems, and distributed video-based surveillance is a good canonical example of this application class. Such applications are interactive, dynamic, stream-based, computationally demanding, and needing real-time or near real-time guarantees. A sense-process-actuate control loop characterizes the behavior of this application class. ASAP is a scalable distributed architecture for a multi-modal sensor network that caters to the needs of this application class. Features of this architecture include (a) generation of prioritization cues that allow the infrastructure to pay selective attention to data streams of interest; (b) virtual sensor abstraction that allows easy integration of multi-modal sensing capabilities; and (c) dynamic redirection of sensor sources to distributed resources to deal with sudden burstiness in the application. In both empirical and emulated experiments, ASAP shows that it scales up to a thousand of sensor nodes (comprised of high bandwidth cameras and low bandwidth RFID readers), significantly mitigates infrastructure and cognitive overload, and reduces false negatives and false positives due to its ability to integrate multi-modal sensing.
27 citations