Showing papers on "Situation awareness published in 2013"

Vessel Pattern Knowledge Discovery from AIS Data: A Framework for Anomaly Detection and Route Prediction

Abstract: Understanding maritime traffic patterns is key to Maritime Situational Awareness applications, in particular, to classify and predict activities. Facilitated by the recent build-up of terrestrial networks and satellite constellations of Automatic Identification System (AIS) receivers, ship movement information is becoming increasingly available, both in coastal areas and open waters. The resulting amount of information is increasingly overwhelming to human operators, requiring the aid of automatic processing to synthesize the behaviors of interest in a clear and effective way. Although AIS data are only legally required for larger vessels, their use is growing, and they can be effectively used to infer different levels of contextual information, from the characterization of ports and off-shore platforms to spatial and temporal distributions of routes. An unsupervised and incremental learning approach to the extraction of maritime movement patterns is presented here to convert from raw data to information supporting decisions. This is a basis for automatically detecting anomalies and projecting current trajectories and patterns into the future. The proposed methodology, called TREAD (Traffic Route Extraction and Anomaly Detection) was developed for different levels of intermittency (i.e., sensor coverage and performance), persistence (i.e., time lag between subsequent observations) and data sources (i.e., ground-based and space-based receivers).

Modeling Human and Organizational Behavior: Application to Military Simulations

Abstract: Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.

Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions

Abstract: Previous research has indicated that high levels of vehicle automation can result in reduced driver situation awareness, but has also highlighted potential benefits of such future vehicle designs through enhanced safety and reduced driver workload. Well-designed automation allows drivers’ visual attention to be focused away from the roadway and toward secondary, in-vehicle tasks. Such tasks may be pleasant distractions from the monotony of system monitoring. This study was undertaken to investigate the impact of voluntary secondary task uptake on the system supervisory responsibilities of drivers experiencing highly-automated vehicle control. Independent factors of Automation Level (manual control, highly-automated) and Traffic Density (light, heavy) were manipulated in a repeated-measures experimental design. 49 drivers participated using a high-fidelity driving simulator that allowed drivers to see, hear and, crucially, feel the impact of their automated vehicle handling. Drivers experiencing automation tended to refrain from behaviours that required them to temporarily retake manual control, such as overtaking, resulting in an increased journey time. Automation improved safety margins in car following, however this was restricted to conditions of light surrounding traffic. Participants did indeed become more heavily involved with the in-vehicle entertainment tasks than they were in manual driving, affording less visual attention to the road ahead. This might suggest that drivers are happy to forgo their supervisory responsibilities in preference of a more entertaining highly-automated drive. However, they did demonstrate additional attention to the roadway in heavy traffic, implying that these responsibilities are taken more seriously as the supervisory demand of vehicle automation increases. These results may dampen some concerns over driver underload with vehicle automation, assuming vehicle manufacturers embrace the need for positive system feedback and drivers also fully appreciate their supervisory obligations in such future vehicle designs.

Mobile Phone Data from GSM Networks for Traffic Parameter and Urban Spatial Pattern Assessment - A Review of Applications and Opportunities

Abstract: The use of wireless location technology and mobile phone data appears to offer a broad range of new opportunities for sophisticated applications in traffic management and monitoring, particularly in the field of incident management. Indeed, due to the high market penetration of mobile phones, it allows the use of very detailed spatial data at lower costs than traditional data collection techniques. Albeit recent, the literature in the field is wide-ranging, although not adequately structured. The aim of this paper is to provide a systematic overview of the main studies and projects addressing the use of data derived from mobile phone networks to obtain location and traffic estimations of individuals, as a starting point for further research on incident and traffic management. The advantages and limitations of the process of retrieving location information and transportation parameters from cellular phones are also highlighted. The issues are presented by providing a description of the current background and data types retrievable from the GSM network. In addition to a literature review, the main findings on the so-called Current City project are presented. This is a test system in Amsterdam (The Netherlands) for the extraction of mobile phone data and for the analysis of the spatial network activity patterns. The main purpose of this project is to provide a full picture of the mobility and area consequences of an incident in near real time to create situation awareness. The first results from this project on how telecom data can be utilized for understanding individual presence and mobility in regular situations and during non-recurrent events where regular flows of people are disrupted by an incident are presented. Furthermore, various interesting studies and projects carried out so far in the field are analyzed, leading to the identification of important research issues related to the use of mobile phone data in transportation applications. Relevant issues concern, on the one hand, factors that influence accuracy, reliability, data quality and techniques used for validation, and on the other hand, the specific role of private mobile companies and transportation agencies.

Revisiting the JDL model for information exploitation

Abstract: The original Joint Directors of Laboratories (JDL) model was developed in the early 90's, with revisits in 1998, and 2004. Today, with new technologies of big data, cloud computing, and machine analytics, there is an ever increasing need for integration of people and machines. The original JDL model focused on the data fusion (correlation, filtering, and association) issues, while today there is an increasing emphasis on an integrated approach to information exploitation over sensors, users, and missions using enterprise architectures, interoperability standards, and intelligence to the edge. Given these recent changes to computation and distributed access, we examine ways for extending the JDL model from 1998 to support exploitation functions and information management for situation awareness, massive data analytics for contextual awareness, and domain-specific needs for mission awareness.

Intention awareness: improving upon situation awareness in human-centric environments

Abstract: As the gap between human and machine shrinks, it becomes increasingly important to develop computer systems that incorporate or enhance existing Situation Awareness. However, these tend to focus on raw quantitative parameters, such as position and speed of objects. When these situations are governed by human actors, such parameters leave significant margins of uncertainty. In this paper, we discuss the potential of applying the characteristics intrinsic to the human actors that comprise a given situation to Situation Awareness, and the capacity that these concepts have to improve situation-aware systems. We argue that intention-aware based systems offer an advantage over situation-aware based systems in that they reduce the informational burden on humans without limiting effectiveness. We argue that computational analysis and tracking of semantic and affective information associated with human actors' intentions are an effective way to minimize miscommunication and uncertainty, particularly in time-sensitive and information-saturated situations.

Assessing the Impact of Insufficient Situation Awareness on Power System Operation

Abstract: Situation awareness is a key factor in preserving power system security, as it enables effective and timely decision-making and reactions by the operators to an incident. Insufficient situation awareness results in a delayed, incorrect or deficient response, endangering power system stability. This factor was actually identified as one of the main causes of several electrical disturbances in the last decade. This paper identifies numerous factors that govern the formation of situation awareness in a power system control center. A multi-state model based on Markov modeling is proposed for assessing the impact of insufficient situation awareness on the probability of power system blackouts. The proposed model considers the level of situation awareness and the state of the information infrastructure. The workings of this model are illustrated using the IEEE 24-bus Reliability Test System.

Enhanced air operations using JView for an air-ground fused situation awareness udop

Abstract: Successful management of air assets coordinates many different types of information sources from the air and on the ground for air transportation safety. An example of a combined air-ground operation is air traffic control (ATC), which requires effective visualization of information for users. In this paper, we demonstrate the use of different visualization techniques to support air-ground coordination to enhance situation awareness. Situation awareness is afforded through strategic collection, fusion and presentation of air, ground, and space data. Visual analytics examples are presented using the Java Viewer (JView) User Defined Operating Picture (UDOP) that utilizes the Airspace Concepts Evaluation System (ACES) for civilian aviation applications.

Dynamic routing intelligent vehicle enhancement system

Abstract: Embodiments of the invention provide a dynamic routing intelligent vehicle enhancement system and method. Intelligent land buoys can be proximately disposed to roadways. Each of the intelligent land buoys can gather situational awareness information about the roadways and one or more vehicles traveling thereon. The intelligent land buoys can compress the situational awareness information. One or more remote computer servers can receive the compressed situational awareness information from the plurality of intelligent land buoys, decompress it, and process the decompressed situational awareness information. The one or more remote computer servers can generate vehicle operational intelligence information based at least on the decompressed situational awareness information, and can transmit the vehicle operational intelligence information to the plurality of intelligent land buoys and/or directly to one or more autonomous or semi-autonomous vehicles.

Unsupervised extraction of knowledge from S-AIS data for maritime situational awareness

Abstract: Automatic vessel behaviour analysis is a key factor for maritime surveillance and relies on an efficient representation of knowledge about vessels activity. Emerging technologies such as space-based AIS provides a new dimension of service and creates a need for new methods able to learn a maritime scene model at an oceanic scale. In this paper, we propose such a framework: a probabilistic normalcy model of vessel dynamics is learned using unsupervised techniques applied on historical S-AIS data and used for anomaly detection and prediction tasks, thus providing functionalities for high-level situational awareness (level 2 and 3 of the JDL).

A concept analysis of situational awareness in nursing.

Abstract: Aim This article reports an analysis of the concept of situational awareness in nursing. Background Situational awareness is a fundamental and well-understood concept used to maintain operational safety in high reliability organizations; however, it has not been studied in nursing. Nurses play a critical role in providing vigilance in health care and what they do or fail to do is directly related to patient outcomes. Data sources Multiple databases, including PubMed, CINAHL, JSTOR, and Google Scholar, were searched with the term, ‘situational awareness’. The primary search, used to identify all uses of the concept, did not employ date criteria. A secondary search for articles measuring situational awareness as an independent or dependent variable was completed using 2009–2011 articles. Design Concept Analysis. Review methods The concept of situational awareness was examined using Walker and Avant's eight step method of analysis. Results Three defining attributes of situational awareness include perception, comprehension, and projection. Situational awareness is defined as the perception of the elements in the environment in a volume of time and space, the comprehension of their meaning and the projection of their status in the near future. Although situational awareness is related to other terms in nursing, there is increasing recognition that the concept, which is likely a consolidation of the related terms, has an impact on healthcare professionals. Conclusion Failures in perception, comprehension, and/or projection can significantly reduce the accuracy and appropriateness of patient care decisions. Therefore, as a precursor to decision making, poor or inadequate levels of situational awareness present serious threats to patient safety. Situational awareness needs to be examined in a theoretical context, studied systematically and openly recognized as a key factor in the delivery of safe patient care.

The road to automated driving: Dual mode and human factors considerations

Abstract: Recent technological developments have shown a transition from informative driving support systems to more automated vehicles. Although automated vehicles are designed to overcome limitations in human perception, decision making and response, there may be a downside to introducing these technologies. The downside is based on the new cooperation between the driver and the vehicle, leaving room for misinterpretation, overreliance on system performance and loss of situation awareness in case of requested transfer of control from the automated vehicle back to the driver. This article raises several human factors issues that are of importance when designing (semi-)automated vehicles, such as: the driver as a system monitor, situation awareness and system limitations. Various implications for the design of automated systems are discussed.

Wide-Area Situational Awareness for Critical Infrastructure Protection

Abstract: Despite successive attempts to protect critical infrastructures against incidents and malicious threats by using traditional situational awareness solutions, the complex and critical nature of these infrastructures makes this adaptation difficult. For this reason, experts are reconsidering the topic of Wide-Area Situational Awareness (WASA) to provide monitoring of performance at all times from anywhere while ensuring dynamic prevention and response services. Given the novelty of this new research field, a WASA methodological framework together with a set of requirements for awareness construction are presented in this paper in order to help in the development and commissioning of future WASA defense solutions.

A System Design for Teleoperated Road Vehicles

Abstract: The possibility to provision road vehicles unmanned and on demand will have an important influence on the development of new mobility concepts. We therefore present the teleoperated driving of road vehicles. This paper outlines the basic concepts, including a static multi-camera design, an operator interface with a sensor fusion based display, and a cellular network based video transmission and communication architecture. We also show how we manage to fulfill the system's technical requirements with our hard- and software design and point out the occurring problems due to communication limitations and lack of situation awareness. Finally, we propose solutions to guarantee driving safety.

The influence of time-criticality on Situation Awareness when retrieving human control after automated driving

Abstract: When applying automated driving as a means for congestion assistance, developers are challenged how to accommodate the transitions between automated and manually driving, especially because these transitions might occur regularly and suddenly. During automated driving, the ability to take over control is also aggravated due to the driver being placed out of the control-loop. To assess then the ability to retrieve human control, we tested within a driver simulator experiment the influence of criticality (available time) on Situation Awareness (SA) gained during time-critical take-overs within a scenario of congested driving. Though one of the applied measurement methods did not show the expected effect of SA on successfulness of taking back control, the results show that drivers are able to successfully retrieve control, also within time-critical situations. Furthermore, the results show that the ability to retrieve control is positively influenced if drivers gain increased levels of SA.

ADS-B for small Unmanned Aerial Systems: Case study and regulatory practices

Abstract: Sense and Avoid Systems (SAASs) are one of the last technical challenges for the safe integration of Unmanned Aerial Systems (UASs) into the U.S. National Airspace System (NAS). While military applications still dominate UAS use, civilian UAS usage is expected to grow dramatically over the next several years. However with this growth, there are significant air safety concerns. SAASs have been proposed as potential solutions for air traffic collisions and obstacle avoidance, but the technical implementations have been largely unsatisfactory. The development of the Next Generation Air Transportation System (NextGen) surveillance tracking technology known as Automatic Dependent Surveillance-Broadcast (ADS-B) has been proposed as one of the potential solutions. This technology, mandated to be in all aircraft by 2020, is designed to improve situational awareness for pilots and improve air traffic management but may also be utilized by UASs. However there remains implementation issues and regulatory issues, especially for small UASs (SUASs) that are expected to be used significantly by civilian operators. This paper examines the use of ADS-B in future SAASs and their implementations in SUAS for domestic use.

User-centered perspectives for automotive augmented reality

Abstract: Augmented reality (AR) in automobiles has the potential to significantly alter the driver's user experience. Prototypes developed in academia and industry demonstrate a range of applications from advanced driver assist systems to location-based information services. A user-centered process for creating and evaluating designs for AR displays in automobiles helps to explore what collaborative role AR should serve between the technologies of the automobile and the driver. In particular, we consider the nature of this role along three important perspectives: understanding human perception, understanding distraction and understanding human behavior. We argue that AR applications should focus solely on tasks that involve the immediate local driving environment and not secondary task spaces to minimize driver distraction. Consistent depth cues should be supported by the technology to aid proper distance judgement. Driving aids supporting situation awareness should be designed with knowledge of current and future states of road users, while focusing on specific problems. Designs must also take into account behavioral phenomena such as risk compensation, inattentional blindness and an over-reliance on augmented technology in driving decisions.

A cloud computing based architecture for cyber security situation awareness

Abstract: The exponential growth of cyber space has created opportunities for world-wide web-based businesses and information sharing, but also led to the proliferation of cyber attacks. To conduct the cyber security situation awareness, a large volume of data streams from monitored devices needs to be efficiently stored and processed in real time. In this paper, we propose a cloud computing based architecture for conducting cyber security situation awareness. Particularly, we leverage the cloud infrastructure with a cost-effective data storage and investigate efficient stream processing techniques to reduce operational delays. To effectively detect threats, we present a parallel cloud based threat detection that integrates both signature-based detection and anomaly-based detection. To capture the insightful characteristics of attacks, we discuss the attack scene analysis based on spatiotemporal correlation and visualization schemes to analyze, trace, and visualize abnormal behaviors. Lastly, we present the testbed setup and the implementation workflow to validate the effectiveness of our proposed system.

A situation model to support awareness in collaborative design

Abstract: The concept of awareness was introduced to underline the importance of shared knowledge and enhance collaborative work. Actors require much knowledge about their work situation and their collaborators' activities in order to complete their own activities successfully. This paper first contributes to a detailed literature review about the concept of awareness. This review helps to identify key awareness-related requirements for the development of collaborative systems. The second contribution is related to the proposal of a generic situation model that is based on the concept of entities, interactions and specific roles. This new conceptual framework intends to favor situation awareness and support shared representations. It concerns both technical and organizational design activities and describes the collaborative situations from multiple views and at different organizational levels (project, team and individual). The proposal's interest and its feasibility for use in the development of collaborative systems are demonstrated by instances related to a case study and by analyzing the potential satisfaction of the identified awareness-related requirements. To sum up, the paper offers a synthesis of key context-related concepts and a generic model for the representation of collaborative situations to increase awareness.

Building shared situational awareness in surgery through distributed dialog

Abstract: Background Failure to convey time-critical information to team members during surgery diminishes members’ perception of the dynamic information relevant to their task, and compromises shared situational awareness. This research reports the dialog around clinical decisions made by team members in the time-pressured and high-risk context of surgery, and the impact of these communications on shared situational awareness. Methods Fieldwork methods were used to capture the dynamic integration of individual and situational elements in surgery that provided the backdrop for clinical decisions. Nineteen semi structured interviews were performed with 24 participants from anaesthesia, surgery, and nursing in the operating rooms of a large metropolitan hospital in Queensland, Australia. Thematic analysis was used. Results: The domain “coordinating decisions in surgery” was generated from textual data. Within this domain, three themes illustrated the dialog of clinical decisions, i.e., synchronizing and strategizing actions, sharing local knowledge, and planning contingency decisions based on priority. Conclusion Strategies used to convey decisions that enhanced shared situational awareness included the use of “self-talk”, closed-loop communications, and “overhearing” conversations that occurred at the operating table. Behaviours’ that compromised a team’s shared situational awareness included tunnelling and fixating on one aspect of the situation.

Traffic knowledge discovery from AIS data

Abstract: Maritime Situational Awareness (i.e., an effective understanding of activities in and impacting the maritime environment) can be significantly improved by knowledge discovery of maritime traffic patterns. The recent build-up of terrestrial networks and satellite constellations of Automatic Identification System (AIS) receivers provides a rich source of cooperative vessel movement information. This vast amount of information can not be fully utilized by human operators and poses new storage and computational challenges. A compact representation of this rapidly increasing amount of information gives operational utility to data which would otherwise be ignored. This paper proposes an unsupervised and incremental learning approach to extract the historical traffic patterns from AIS data. The presented methodology called Traffic Route Extraction for Anomaly Detection (TREAD) effectively processes raw AIS data to infer different levels of contextual information, spanning from the identification of ports and off-shore platforms to spatial and temporal distributions of traffic routes. Furthermore, the accurate understanding of the historical traffic enables the classification and prediction of vessel behaviours as well as the detection of low-likelihood behaviours, or anomalies. The ultimate goal is to provide operators with a configurable knowledge framework supporting day by day decision making and general awareness of vessel pattern of life activity. The methodology is demonstrated via a real-world case study, which can be used as a reference data set for further analysis.

Building shared situational awareness in surgery through distributed dialog

Abstract: Excellence in Nursing Interventions for Hospitalized Patients (NCREN) Research Centre for Clinical and Community Practice INHMRC Centre of Research Innovation (RCCCPI), Griffith Health Institute, Griffith University Queensland, AustraliaCorrespondence: Brigid M Gillespie milieu of the operating roomNational Health and Medical Research Council Centre for Excellence in Nursing Interventions, Research Centre for Clinical and Community Practice Innovation, Griffith Health Institute, Brisbane, Queensland, Australia 3Tel +617 5552 9718 Fax +617 5552 8526 Email b.gillespie@griffith.edu.au

Opportunistic spatio-temporal event processing for mobile situation awareness

Abstract: With the proliferation of mobile devices and sensors, mobile situation awareness is becoming an important class of applications. The key requirement of this class of applications is low-latency processing of events stemming from sensor data in order to provide timely situational information to mobile users. To satisfy the latency requirement, we propose an opportunistic spatio-temporal event processing system that uses prediction-based continuous query handling. Our system predicts future query regions for moving consumers and starts processing events early so that the live situational information is available when the consumer reaches the future location. In contrast to existing systems, our system provides timely information about a consumer's current position by hiding computation latency for processing recent events. To evaluate our system, we measure the quality of results and timeliness of live situational information with various query parameters. Our evaluation shows that we can achieve highly meaningful query results with near-zero latency in most cases.