Distributed Situation Awareness Research Articles

Representing and assessing distributed situation awareness in multi-agency disaster response: A hypergraph-based methodology

This paper introduces a novel hypergraph-based methodology for representing and assessing distributed situation awareness (DSA) in multi-agency disaster response. The fundamental ideas and motivations of our methodology stem from the following widely acknowledged understandings and phenomenons: (a) DSA’s representation should be approached from social, information and task dimensions; (b) DSA is one of the collective behaviors that emerge from the interactions; (c) the interactions in the real world are not pairwise. Our methodology delineates the collaboration, co-activation, and co-existence interactions among social, information, and task elements as higher-order interactions. We then construct these interaction systems using hypergraph-structured data derived from disaster response scenarios. Subsequently, these systems are encoded into hypergraphs, which are validated against our dataset and proven to be practical tools for depicting higher-order interaction patterns. Analytical techniques tailored to hypergraphs are applied, yielding insights intrinsic to hypergraphs regarding DSA in emergency response. Moreover, we integrate these interaction systems into a comprehensive framework that allows for the visualization and quantitative analyses of DSA evolution dynamics. We propose several indicators of evolution, discussing their trends and implications throughout the development of the emergency response. We locate the system deficiencies by revealing a mismatch between the positions of specific elements in the network and their functions. We also identify the saturation phase in the DSA evolution process.

An mHealth Design to Promote Medication Safety in Children with Medical Complexity.

Children with medical complexity (CMC) are uniquely vulnerable to medication errors and preventable adverse drug events because of their extreme polypharmacy, medical fragility, and reliance on complicated medication schedules and routes managed by undersupported family caregivers. There is an opportunity to improve CMC outcomes by designing health information technologies that support medication administration accuracy, timeliness, and communication within CMC caregiving networks. The present study engaged family caregivers, secondary caregivers, and clinicians who work with CMC in a codesign process to identify: (1) medication safety challenges experienced by CMC caregivers and (2) design requirements for a mobile health application to improve medication safety for CMC in the home. Study staff recruited family caregivers, secondary caregivers, and clinicians from a children's hospital-based pediatric complex care program to participate in virtual codesign sessions. During sessions, the facilitator-guided codesigners in generating and converging upon medication safety challenges and design requirements. Between sessions, the research team reviewed notes from the session to identify design specifications and modify the prototype. After design sessions concluded, each session recording was reviewed to confirm that all designer comments had been captured. A total of N = 16 codesigners participated. Analyses yielded 11 challenges to medication safety and 11 corresponding design requirements that fit into three broader challenges: giving the right medication at the right time; communicating with others about medications; and accommodating complex medical routines. Supporting quotations from codesigners and prototype features associated with each design requirement are presented. This study generated design requirements for a tool that may improve medication safety by creating distributed situation awareness within the caregiving network. The next steps are to pilot test tools that integrate these design requirements for usability and feasibility, and to conduct a randomized control trial to determine if use of these tools reduces medication errors.

A Novel Distributed Situation Awareness Consensus Approach for UAV Swarm Systems

A Novel Distributed Situation Awareness Consensus Approach for UAV Swarm Systems

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In the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge is gathered incrementally and in different ways by heterogeneous robots and humans. The purpose of this paper is to describe an RDF Graph Synchronization System called RGS⊕\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\oplus $$\\end{document}. It is assumed that a dynamic set of agents provide or retrieve knowledge stored in their local RDF Graphs which are continuously synchronized between agents. The RGS⊕\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\oplus $$\\end{document} System was designed to handle unreliable communication and does not rely on a static centralized infrastructure. It is capable of synchronizing knowledge as timely as possible and allows agents to access knowledge while it is incrementally acquired. A deeper empirical analysis of the RGS⊕\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\oplus $$\\end{document} System is provided that shows both its efficiency and efficacy.

UAV Swarm Cooperative Situation Awareness Theory Model Construction and Scenario Analysis

The Unmanned Aerial Vehicle (UAV) swarm collaborative operations is one of the disruptive technologies in future information warfare. Considering the characteristics of UAV swarm collaborative operation, we propose two UAV swarm cooperative situation awareness (SA) theory models based on the classical ones and the composition of UAV swarm. Firstly, the improved Endsley three-level SA model is proposed, in which the traditional mental model is changed into human machine intelligent model on the individual level. Then the homogeneous swarm and heterogeneous swarm cooperative SA model are separately built based on the improved team SA model and Distributed SA (DSA) model. Meanwhile, a comparison between the multi-UAV and UAV swarm is carried. Finally, a scenario analysis of swarm cooperative SA in combat situation is presented.

Modeling and simulation for situation awareness distribution and transactions for intrahospital patient transports

Intrahospital transports rely on effective transmission of information between medical staff and information systems to support Distributed Situation Awareness (DSA) on patient status and transport requirements. This study presents the preliminary results a simulation model combining discrete event simulation (DES) and agent-based modeling (ABM) to quantify SA distribution and transactions for intrahospital transportation. The simulation model captured the transport requests, transport processes, and knowledge distribution and transactions between (human or machine) agents for intrahospital transports. Specifically, this paper presents the simulation results for the successful patient transport from 17 hospital inpatient units to the radiology department for (1) transport times and (2) transport cancellations. One-way t-tests did not reveal any significant differences in average transport time and number of cancelations between outputs of 100 simulation replications and historical data for 18-month operation. These results indicate that the simulation model represents real-world operation that can subsequently be used to test potential intervention to improve DSA in patient flow.

Understanding situation awareness in SOCs, a systematic literature review

Situation awareness is shown through human factors research to be a valuable construct to understand and improve how humans perform while operating complex systems in critical environments. Within cyber security one such environment is the Security Operations Center (SOC). With the increasing threat of hybrid warfare, knowledge about situation awareness within SOC environments, where human error or low performance may be detrimental, must be developed. This paper reports on the results of a Systematic Descriptive Literature Review of the current research on situation awareness within SOCs. The goal of the paper is to analyze how situation awareness is understood in the current research. To achieve this goal three aspects of understanding were addressed: Theoretical foundations; levels of conceptualization; and measurement of situation awareness. Theoretical foundations in the literature were assessed by how situation awareness was defined and the presence of references to theoretical models of SA. The results show a clear trend of basing the research on Endsley's three level situation awareness model; this model has been developed into a domain specific formulation called “Cyber Situation Awareness”. Some parts of the literature, particularly in research aimed at developing tools for improving situation awareness, lack a theoretical foundation; some refer to alternative theoretical foundations of situation awareness like Stanton et al.’s Distributed Situation Awareness. Further, a balance between conceptualizations on the individual, group and system level has been identified. Within research aimed at developing tools for improving situation awareness there are some examples of specialized and precise measurements of situation awareness, but in general the research seems too reliant on indirect measures of situation awareness. The paper concludes with the proposition of connecting the systems-based theoretical perspective of distributed situation awareness into the research, utilizing a systems level conceptualization of situation awareness. This might prove to be a useful bridge between the human cognitive perspective of situation awareness and the development of the complex technical environment of critical importance that SOCs represent.

Formalizing Distributed Situation Awareness in Multi-Agent Networks

The version of distributed situation awareness (DSA) used in this article originated in human factors/ergonomics. Typically, this has involved the study of human operators working in teams and has used various forms of concept maps to qualitatively describe the information that team members use. In this article, we apply the concept of DSA to multi-agent teams (where team members might be human or automation) and extend the concept using the formal properties of Bayesian belief networks. In particular, we show how the Bayesian belief network can define DSA and how such a network can (using expectation maximization) adapt, even on the basis of limited information. The approach was considered in terms of situation awareness levels of perception (i.e., sensor state values conversion to belief) and projection (in terms of prediction and mission missing values estimation accuracy).

Interdependence Analysis in collaborative robot applications from a joint cognitive functional perspective

This paper sets up a framework to assess co-agency in human-robot interactions, and applies it specifically to the socio-technical safety analysis of collaborative robots. We also examine to what extent the concept of Situation Awareness can be applied to assess collaborative robots as efficient team members in socio-technical systems. We explain some theoretical concerns with traditional concepts of Situation Awareness and defend why the concept of Joint Cognitive Systems, which maps the conceptualization of the cognitive system onto the work system as a whole, is best suited for issues of distributed cognition and controllability in human-robot interaction. Thereafter we present a five-step methodology specifically conceived for cobot applications serving the aim of goal coordination between multiple agents by functional interactions. The proposed framework merges two existing safety and resilience analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. These methods are used in combination to assess shared control in safe and efficient human-robot interaction from a systems-thinking perspective. This allows to describe the systemic conditions for Distributed Situation Awareness in terms of observable system interactions and as an emergent object of distributed cognition. Instead of looking at undesirable safety outcomes, we have imposed the focus of co-agency as the unit of analysis in line with the Joint Cognitive Systems perspective. The theoretical insights from this paper are additionally applied to a hypothetical but credible demonstration case study with collaborative warehouse robots.

AAIM Recommendations to Improve Learner Transitions

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Hastily formed knowledge networks and distributed situation awareness for collaborative robotics

In the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge are gathered incrementally and in different ways by heterogeneous robots and humans. We describe this as the creation of Hastily Formed Knowledge Networks (HFKNs). The focus of this paper is the specification and prototyping of a general distributed system architecture that supports the creation of HFKNs by teams of robots and humans. The information collected ranges from low-level sensor data to high-level semantic knowledge, the latter represented in part as RDF Graphs. The framework includes a synchronization protocol and associated algorithms that allow for the automatic distribution and sharing of data and knowledge between agents. This is done through the distributed synchronization of RDF Graphs shared between agents. High-level semantic queries specified in SPARQL can be used by robots and humans alike to acquire both knowledge and data content from team members. The system is empirically validated and complexity results of the proposed algorithms are provided. Additionally, a field robotics case study is described, where a 3D mapping mission has been executed using several UAVs in a collaborative emergency rescue scenario while using the full HFKN Framework.

Distributed situation awareness: From awareness in individuals and teams to the awareness of technologies, sociotechnical systems, and societies

A large component of Neville Stanton's work has focused on situation awareness in domains such as defence, transport, and process control. A significant contribution has been to initiate a shift from considering individual human operator situation awareness to considering the situation awareness of human and non-human teams, organisations, and even sociotechnical systems. Though controversial when introduced, the distributed situation awareness model has become increasingly relevant for modern day systems and problems. In this article we reflect on Stanton's contribution and point to a pressing need to consider a. The situation awareness of advanced technologies, and b. situation awareness at a sociotechnical system, societal and even global level. This is demonstrated via discussion on two contemporaneous issues: automated vehicles and the COVID-19 pandemic. It is concluded that, given advances such as artificial intelligence, the increased connectedness of society, emerging issues such as disinformation, and an increasing set of global threats, Stanton's distributed situation awareness model and associated analysis framework provide a useful toolkit for future Human Factors and Ergonomics applications.

Using Bayesian belief networks to improve distributed situation awareness in shift changeovers: A case study

This paper presents a case study about communication between workers during shift changes based on empirical research at a continuously operating industrial operation.The premises of Situation Awareness (SA) and Distributed Situation Awareness (DSA) are the theoretical lens for conducting the present study. The objective of the study is the probabilistic modeling of the SA of process operators by means of complementarity among the premises of SA and DSA during shift change.The methodology used semi-structured interviews that followed a questionnaire created to categorize verbalizations at the three SA levels. Verbalizations were analyzed with the “digital humanities” approach that allowed the integrated modeling of SA using Bayesian Belief Networks (BBN) theory. The research was performed in an industrial plant that carried out a polymer injection process, which was classified as a physical arrangement for the continuous manufacture of products. In this process, production was conducted in three continuous shifts with one operator per shift.As a result, the BBN modeling showed the dynamic relationships among the core variables monitored, and also demonstrated the complementarity between SA and DSA. In this sense, BBN was used as a communication protocol between shifts and served as a mechanism that influences the operator’s cognitive load. The developed algorithm showed an excellent performance, because it represents the conditional probability between the variables according to the operators' indications regarding the criticality and level of monitoring of the process. The modeling allowed representing the operators’ complete SA, thus promoting DSA.

Distributed Situation Awareness for Multi-agent Mission in Dynamic Environments: A Case Study of Multi-UAVs Wildfires Searching

This thesis focuses attention on achieving Distributed Situation Awareness (DSA) with minimal resources (energy, processing cost, etc.) using small low-capacity agents (e.g., UAVs) coordinated in a decentralised fashion while conducting searching activity. This is in contrast to the existing works involving convoluted communication and information processing.

Collaborating AI and human experts in the maintenance domain

Maintenance decision errors can result in very costly problems. The 4th industrial revolution has given new opportunities for the development of and use of intelligent decision support systems. With these technological advancements, key concerns focus on gaining a better understanding of the linkage between the technicians’ knowledge and the intelligent decision support systems. The research reported in this study has two primary objectives. (1) To propose a theoretical model that links technicians’ knowledge and intelligent decision support systems, and (2) to present a use case how to apply the theoretical model. The foundation of the new model builds upon two main streams of study in the decision support literature: “distribution” of knowledge among different agents, and “collaboration” of knowledge for reaching a shared goal. This study resulted in the identification of two main gaps: firstly, there must be a greater focus upon the technicians’ knowledge; secondly, technicians need assistance to maintain their focus on the big picture. We used the cognitive fit theory, and the theory of distributed situation awareness to propose the new theoretical model called “distributed collaborative awareness model.” The model considers both explicit and implicit knowledge and accommodates the dynamic challenges involved in operational level maintenance. As an application of this model, we identify and recommend some technological developments required in augmented reality based maintenance decision support.

Quantitative Evidence Supporting Distributed Situation Awareness Model of Patient Flow Management

Quantitative Evidence Supporting Distributed Situation Awareness Model of Patient Flow Management

Cognition in crisis management teams: an integrative analysis of definitions

In large-scale extreme events, multidisciplinary crisis management teams (CMTs) are required to function together cognitively. Despite theoretical maturity in team cognition and recurrent emphasis on cognition in the crisis management practices, no synthesis of theoretical and practical discourses is currently available, limiting empirical investigations of cognition in CMTs. To address this gap, this paper aims to review the definitions of cognition in CMTs, with a particular focus on examining if and to what extent they are diversified. Through a systematic process to search peer-reviewed journal articles published in English from 1990 to 2019, 59 articles were selected with 62 coded definitions of 11 different constructs. The similarities and variabilities of the definitions were examined in terms of their theoretical and practical emphases and then synthesised into an integrative definition expected to serve as a general guide of reference for future researchers seeking an operational definition of cognition in CMTs. Practitioner summary: Understanding of cognition in CMTs is grounded in various theories and models with varying assumptions. An integrative conceptualisation of such cognition as interaction within and across CMTs to perceive, diagnose, and adapt to the crisis may facilitate the accumulation of knowledge and future operationalisations. Abbreviations: CMT(s): crisis management team(s); SMM: shared mental model; TMM: team mental model; COP: common operating picture; SSA: shared situation awareness; TSA: team situation awareness; DC: distributed cognition; ITC: interactive team cognition; TMS: transitive memory system(s); DSA: distributed situation awareness

Distributed situation awareness: a health-system approach to assessing and designing patient flow management

Patient flow management is a system-wide process but many healthcare providers do not integrate multiple departments into the process to minimise the time between treatments or medical services for maximum patient throughput. This paper presents a case study of applying Distributed Situation Awareness (DSA) to characterise system-wide patient flow management and identify opportunities for improvements in a healthcare system. This case study employed a three-part method of data elicitation, extraction, and representation to investigate DSA. Social, task, and knowledge networks were developed and then combined to characterise patient flow management and identify deficiencies of the command and control centre of a healthcare facility. Social network analysis provided centrality metrics to further characterise patient flow management. The DSA model helped identify design principles and deficiencies in managing patient flow. These findings indicate that DSA is promising for analysing patient flow management from a system-wide perspective. Practitioner summary: This article examines Distribution Situation Awareness (DSA) as an analysis framework to study system-wide patient flow management. The DSA yields social, task, and knowledge networks that can be combined to characterise patient flow and identify deficiencies in the system. DSA appears promising for analysing communication and coordination of complex systems. Abbreviations: CDM: critical decision method; CTaC: carilion transfer and communications center; EAST: event analysis systematic teamwork; ED: emergency department; DES: discrete event simulation; DSA: distributed situation awareness; SA: situation awareness; SNA: social network analysis

A new approach to requirement development for a common operational picture to support distributed situation awareness

In a safety–critical socio-technical system with Distributed Situation Awareness (DSA), it is important to secure effective communication among a number of agents for safe accomplishment of missions. Sharing a common mental model is essential for correct and efficient communication. A Common Operational Picture (COP), based on the network-based information technology, facilitates a shared mental model of the overall situation of the system for better cooperation in system-wide missions. The mental model of the functional structure of the system is very important because each user with a particular task and viewpoint has to access the COP where all system information is centralized and updated in real time. While avoiding information overload, a user should be able to recognize the relevant information intuitively according to one’s role and context and also access the information held by other users without confusion. In this paper, we describe a safety-oriented design process for a COP of weapon test missions that aims to support sharing of the mental model and efficient communication while controlling possible propagation of variability among the functions of the system. The multi-layered organization of system functions are analyzed by Work Domain Analysis (WDA) and the potential interaction among the functions in terms of variability is modeled by Functional Resonance Analysis Method (FRAM). The COP requirements developed by the proposed method include important design points that the previous system has missed. Finally, an exemplar COP design that dynamically presents the system status according to Abstraction Hierarchy (AH) and functional relations to facilitate a shared mental model and situation awareness is shown.

Automated Vehicle Handover Interface Design: Focus Groups with Learner, Intermediate and Advanced Drivers

Conditionally and highly automated vehicles will require drivers to take control as a result of a non-emergency, such as a geographical, terrain, capability or design boundary. It is anticipated that these events will provide the driver with a sufficient amount of time to prepare themselves for the transition of control. This study explores conditionally and highly automated vehicle transitions of control by asking how drivers of differing skill levels (learner, intermediate and advanced) approach the task of designing an interface responsible for making transitions safer, more usable and more efficient. Three focus groups generated detailed designs for vehicle-to-driver transitions in an 1-h and a 10-min “out-of-the-loop” scenarios and transitions from driver to vehicle. Results show great variation in the approaches taken by each skill group (e.g., the reliance on visual interfaces for awareness assist and viewpoints on issues such as multimodal displays). Customization was a common theme throughout, with drivers desiring the option to adjust alert timings and modalities in which information is displayed. This paper presents these designs along with a detailed comparison of group designs and implements distributed situation awareness theory to discuss findings and draw conclusions.