Vehicle-to-Vehicle communication is the key technology for achieving increased perception for automated vehicles where the communication allows virtual sensing with the use of sensors placed in other vehicles. In addition, this technology also allows recognising objects that are out-of-sight. This thesis presents a Trust System that allows a vehicle to make more reliable and robust decisions. The system evaluates the current situation and generates a Trust Index indicating the level of trust in the environment, the ego vehicle, and the other vehicles. Current research focuses on securing the communication between the vehicles themselves, but does not verify the content of the received data on a system level. The proposed Trust System evaluates the received data according to sensor accuracy, behaviour of other vehicles, and the perception of the local environment. The results show that the proposed method is capable of correctly identifying various situations and discusses how the Trust Index can be used to make more robust decisions.

A Computação Ubíqua (UbiComp) foi introduzida na década de 90 como a área de pesquisa que estuda a integração da tecnologia às tarefas cotidianas, com a intenção de proporcionar aos usuários a manutenção do foco em suas atividades, reduzindo a necessidade de seu envolvimento com a gerência da infraestrutura computacional. Considerando esta perspectiva de integração das tecnologias, exigindo o mínimo de participação do usuário, um dos desafios centrais de pesquisa para contemplar essa proposta da UbiComp é a Ciência de Situação. A construção do suporte à Ciência de Situação para as aplicações ubíquas envolve a representação do contexto, a coleta, o armazenamento e o processamento dos dados contextuais, bem como a identificação e disseminação das situações, de forma autônoma. Dentre as maneiras que tem sido consideradas para materializar a UbiComp, vem se destacando a Internet das Coisas (Internet of Things - IoT). Esta abordagem utiliza a Internet como principal meio para interoperação entre dispositivos computacionais. Nesse sentido, a IoT tem como premissa unir o mundo físico ao digital, preconizando a ideia do “tudo conectado”, criando assim uma rede de objetos incorporados ao ambiente de forma ubíqua. Deste modo, esta tese tem como objetivo conceber uma arquitetura para provimento de Ciência de Situação às aplicações ubíquas, na perspectiva da infraestrutura da Internet das Coisas. A arquitetura, denominada SAUI (Situation-aware Architecture for Ubiquitous applications in the Internet of things), é concebida considerando os trabalhos previamente desenvolvidos pelo grupo de pesquisa GPPD/UFRGS, particularmente o middleware EXEHDA (Execution Environment for Highly Distributed Applications) Entende-se como contribuições centrais desta tese: (i) a definição de uma abordagem híbrida para representação e processamento do contexto, visando à identificação de situações de interesse das aplicações; e (ii) a concepção de uma arquitetura distribuída, baseada em eventos e regras, visando o suporte à Ciência de Situação das aplicações ubíquas, considerando a infraestrutura provida pela IoT. As funcionalidades da Arquitetura SAUI são avaliadas através de cenários de uso nas áreas de agropecuária e saúde, sendo caracterizados os protótipos desenvolvidos, as tecnologias empregadas e os testes realizados. Os resultados obtidos corroboram com a abordagem da Arquitetura SAUI de considerar um suporte concomitante para operação distribuída, tratamento autônomo dos dados contextuais baseado em eventos e regras, e processamento híbrido do contexto, visando à identificação de situações de interesse das aplicações. / The Ubiquitous Computing (UbiComp) was introduced in the 90s as the area of research that studies the integration of technology in the everyday tasks, with the objective to keep the focus of the users in their activities, reducing the need of their involvement in the management of the computational infrastructure. Considering this perspective of technologies integration, requiring minimal user participation, one of the central research challenges is the situation awareness. The construction of the support to situation awareness for ubiquitous applications involves the representation of context; the acquisition, storage and processing of contextual data; and the identification and dissemination of situations, in autonomous way. Among the ways that have been considered to materialize UbiComp, has been highlighting the IoT (Internet of Things). This approach uses the Internet as the main means for interoperation between computing devices. In this sense, the IoT has the premise of join the physical and digital worlds, contemplating the idea of “everything connected”, thus creating a network of objects embedded in the environment ubiquitously. Thus, this thesis aims to design an architecture for providing situation awareness to ubiquitous applications, considering the IoT infrastructure. The architecture, called SAUI (Situation-aware Architecture for Ubiquitous applications in the Internet of things), is designed considering the work previously developed by the research group GPPD/UFRGS, particularly EXEHDA middleware (Execution Environment for Highly Distributed Applications) It is considered as central contributions of this thesis: (i) the definition of a hybrid approach for modeling and processing of context, aiming at identification of situations of interest of the applications; and (ii) the design of a distributed architecture, driven by events and rules, aiming at supporting the situation awareness of ubiquitous applications, considering an IoT infrastructure. The funcionalities of SAUI architecture are evaluated through usage scenarios in the areas of agriculture and healthcare. It was characterized the developed prototypes, the technologies used, and the tests performed. The results corroborate with the approach of SAUI architecture, which considers a concomitant support for distributed operation, autonomous handling of context based on events and rules, and hybrid processing of context, aiming at identification of situations.

Crew coordination in the context of aviation is a specifically choreographed set of tasks performed by each pilot, defined for each phase of flight. Based on the constructs of effective Crew Resource Management and SOPs for each phase of flight, a shared understanding of crew workload and task responsibility is considered representative of well-coordinated crews. Nominal behavior is therefore defined by SOPs and CRM theory, detectable through pilot eye-scan. This research investigates the relationship between the eye-scan exhibited by each pilot and the level of coordination between crewmembers. Crew coordination was evaluated based on each pilot's understanding of the other crewmember's workload. By contrasting each pilot's workload-understanding, crew coordination was measured as the summed absolute difference of each pilot's understanding of the other crewmember's reported workload, resulting in a crew coordination index. The crew coordination index rates crew coordination on a scale ranging across Excellent, Good, Fair and Poor. Eye-scan behavior metrics were found to reliably identify a reduction in crew coordination. Additionally, crew coordination was successfully characterized by eye-scan behavior data using machine learning classification methods. Identifying eye-scan behaviors on the flight deck indicative of reduced crew coordination can be used to inform training programs and design enhanced avionics that improve the overall coordination between the crewmembers and the flight deck interface. Additionally, characterization of crew coordination can be used to develop methods to increase shared situation awareness and crew coordination to reduce operational and flight technical errors. Ultimately, the ability to reduce operational and flight technical errors made by pilot crews improves the safety of aviation.

Pilots are subject to varying levels of stress, workload, and fatigue during long flights. During different phases of a commercial flight, pilots are engaged in multiple tasks which include going through checklists, checking conditions at their destination, communicating with Air Traffic Control and dealing with other flight related tasks. The amount of work varies from the earlier stages until the end of the flight. It is not well understood how changes in the amount of workload can affect a pilot's ability to engage with important tasks that relate to safety of flight. The work shown in this thesis focused on the level of engagement displayed by flight crew as a function of level of workload. The principal hypothesis was that very low levels of workload may lead to crew disengagement and sub-optimal levels of performance. The degree to which pilots remain alert and are fatigued during a commercial flight is also not established in a concrete way.

Experienced and novice simulator pilots are subject to some of the constraints of a real flight (or a full flight simulator) situation in a PC based flight simulation. In this thesis, the effects of expertise, working memory capacity, inhibition and divided attention on situation awareness (SA) in simulated flight task environments are investigated. The cognitive aspects underlying the process of situation awareness are explored by analyzing the compound effects of above listed factors. Online and Offline SA measurements obtained from a simulated flight task are used with flight hours standing for expertise and scores of Automated Operation Span Task, Stroop and Coskun&ouml / z visual attention tasks as measurements for working memory capacity, inhibition and divided attention respectively. Regression analyses reveal that expected relationships of simulator pilots&rsquo / SA with expertise and inhibition capacity are supported. On the other hand, expected relationships of SA with working memory and divided attention capacities are not revealed. This situation probably results from unsystematic differences in simulator pilots&rsquo / practices. In addition to the main experiment, simulator pilots&rsquo / levels of neural activity at their dorsolateral prefrontal cortex are also measured during their behavioral performance. The relationships among neural correlates of mental workload induced by the simulated flight are investigated by the functional near-infrared (fNIR) spectroscopy optical brain imaging technology. Theorized mental workload distinction in the scenario of the simulated flight task is successfully observed in both perceived workload declarations and oxygenation measurements by fNIR.

Advances in information technology produce large sets of data for decision makers. In both military and civilian efforts to achieve decision superiority, decision makers have to act agilely with proper, adequate and relevant information available. Information fusion is a process aimed to support decision makers’ situation awareness. This involves a process of combining data and information from disparate sources with prior information or knowledge to obtain an improved state estimate about an agent or other relevant phenomena. The important issue in decision making is not only assessing the current situation but also envisioning how a situation may evolve. In this work we focus on the prediction part of decision making called predictive situation awareness. We introduce new methodology where simulations and plan recognition are tools for achieving improved predictive situation awareness. Plan recognition is the term given to the process of inferring an agent’s intentions from a set of actions and is intended to support decision making. Beside its main task that is to support decision makers’ predictive situation awareness, plan recognition could also be used for coordination of actions and for developing computer-game agents that possess cognitive ability to recognize other agents’ behaviour. Successful plan recognition is heavily dependent on the data that is supplied. Therefore we introduce a bridge between plan recognition and sensor management where results of our plan recognition are reused to the control of, to give focus of attention to, the sensors that are expected to acquire the most important/relevant information. Our methodologies include knowledge representation, embedded stochastic simulations, microeconomics, imprecise knowledge and statistical inference issues. / QC 20100922

Investigations into past accidents at nuclear power generating facilities such as that of Three Mile Island have identified human factors as one of the foremost critical aspects in plant safety. Errors resulting from limitations in human information processing are of particular concern for human-machine interfaces (HMI) in plant control rooms. This project examines the application of Ecological Interface Design (EID) in HMI information displays and the effects on operator situation awareness (SA) for turbine secondary systems based on the Swedish Forsmark 3 boiling-water reactor nuclear power plant. A work domain analysis was performed on the turbine secondary systems yielding part-whole decomposition and abstraction hierarchy models. Information display requirements were subsequently extracted from the models. The resulting EID information displays were implemented in a full-scope simulator and evaluated with six licensed operating crews from the Forsmark 3 plant. Three measures were used to examine SA: self-rated bias, Halden Open Probe Elicitation (HOPE), and Situation Awareness Control Room Inventory (SACRI). The data analysis revealed that operators achieved moderate to good SA; operators unfamiliar with EID information displays were able to develop and maintain comparable levels of SA to operators using traditional forms of single sensor-single indicator (SS-SI) information displays. With sufficient training and experience, operator SA is expected to benefit from the knowledge-based visual elements in the EID information displays. This project was researched in conjunction with the Cognitive Engineering Laboratory at the University of Toronto and the Institute for Energy Technology (IFE) in Halden, Norway.

This thesis presents a preliminary goal oriented modeling of situation awareness in a command and control system. Tropos, an agent oriented software development methodology, has been used for modeling. Use of Tropos allows us to represent, at the knowledge level, the Command and Control actors along with their goals and interdependencies. Through refinement we aim to derive an architectural design for the Situation Awareness component of an Air Defense Command and Control system. This work suggests that goal oriented methodologies can be successfully used in the modeling of the complex systems at the requirement analysis phase. By analyzing dependencies between Command and Control entities, it should be possible to improve the modularity of the Command and Control system architecture.

Situation Awareness (SA), is defined as perception of environmental entities, comprehension of their meaning, and estimation of their status in the near future (Endsley, 1995a). The general aim of the study is to investigate the relationship between SA and individual cognitive dierences. Specifically, the predictive value of working memory and attentional capacity measures on SA measures, taken from pilots of different expertise levels, is of interest. In the literature, SA has mostly been studied from an applied perspective. The present study therefore aims at providing the necessary cognitive underpinnings of these more applied studies. Two experiments were conducted. In Experiment 1, individual dierences and SA measures have been taken from thirty-six pilots. Automated Operation Span, Stroop Task, and Choice Reaction Time Task with Dichotic Listening were used for measuring working memory capacity (WMC), inhibition, and divided attention, respectively. Online and offline SA measurements were employed together for tapping on different aspects of SA in a cognitively demanding flight scenario. Results showed that WMC and expertise explain 58% of variability in offline scores while inhibition, divided attention, and expertise explain 52% of variability in online scores. In Experiment 2, the aim was to find correlates of eye movements in terms of individual differences. Scan patterns were studied across four SA-related visual tasks with ten expert pilots. Results showed that more expert pilots produced less fixation durations but no other eects of individual dierences on the eye movements were observed. It was also observed that expert pilots deploy some scan strategies while performing these tasks.

<p>Att uppnå situationsmedvetenhet kan helt avgöra ifall en person klarar av att lösa en specifik uppgift eller inte. Dagens ledningssystem har ofta som uppgift att stödja användaren att upp nå situationsmedvetenhet och därmed klara av att lösa sina uppgifter. Detta examensarbete syftar till att undersöka vilka potentiella brister det kan tänkas finnas inom de militära och civila ledningssystemen. Att lista dessa problem är av intresse då det är av stor vikt att kunna se hur dessa system skulle kunna tänkas förbättras. Både utvecklare och användare har intervjuats i syfte att samla in viktiga åsikter. Resultatet blev en lista där de största problemen redovisades samt vilken inverkan de kan tänkas ha på användaren och dennes arbetsuppgifter.</p>