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With advances in artificial intelligence, machine learning, and cognitive modelling, unmanned aircraft are expected to actas human-like wingmen in the near future. For fluent and effective manned–unmanned teaming, synthetic wingmen must beable to account for and adapt to their partners’ intent with little or no communication. To enable such abilities, it becomescrucial to identify the requirements that makes intent explainable to synthetic wingmen, necessitating approaches to describeand analyse intent from a human-centric perspective. To address this issue, this paper reports on findings from using WorkDomain Analysis to design and analyse models of situated intent with six levels of cognitive control (frames, effects, values,generic, implementations, and physical). Through a literature review and seven subject matter expert interviews, a synthesizedmodel was designed to represent fighter pilots’ intent in a manned–unmanned teaming scenario. Using the synthesized modelas the context, a transfer of control and a link loss situation were further described and analysed. Experiences show that WorkDomain Analysis can provide a practical and applicable means to model situated intent, particularly since designed modelscan be re-utilised to model intent in similar situations. Furthermore, the model analyses show the importance of accountingfor fighter pilots’ adopted frames since small variations of the framing of the situations can propagate throughout the modelresulting in conflicting or inconsistent intent. The paper concludes that synthetic wingmen must be able to reason about all six levels of cognitive control, requiring a more holistic approach to make intent explainable., Funding: VINNOVA; Swedish Defence Material Administration [2017-04884,2017-04884,2017-04884,2017-04884]; NFFP (National Aviation Research Programme) - VINNOVA (Swedish Governmental Agency for Innovation Systems); Swedish Armed Forces, The Swedish Defence Material Administration and NFFP (National Aviation Research Pro- gramme), which is funded by VINNOVA (Swedish Governmental Agency for Innovation Systems, 2017-04884,2017-04884,2017- 04884,2017-04884), the Swedish Armed Forces, and the Swedish Defence Material Administration.

In industrial applications where the physical parameters are highly interconnected, keeping the process flow steady is a major concern for the operators. This is caused by the sensitivity of system to the process dynamics. As a result, a slight adjustment to a control parameter can significantly affect the efficiency of the system and thus impact the financial gain. Paper pulp production is an example of such a process, where operators continuously investigate the potential of changes in the process and predict the consequences of an adjustment before making a decision. Process parameter adjustments prescribed by simulated control models cannot be fully trusted as the external disturbances and the process inherent variabilities cannot be fully incorporated into the simulations. Therefore, to assess the viability of a strategy, operators often compare the situation with the historical records and trends during which the processes in the plant ran steadily. While previous research has mostly focused on developing advanced control models to simulate complex pulp production process, this work aims to support operators analytical reasoning by provision of effective data visualization. The contributions of our design study include a domain problem characterization and a linked-view visual encoding design, which aims to enhance operator's mental models independent of particular users or scenarios. Finally, by reflecting on the advantages of our choice of task abstraction technique, inherited from the ecological interface design framework [5], we reason for the generalizability of our approach to similar industrial applications., Funding agencies: The Sweden’s Innovation Agency (Vinnova) under the project EXPLAIN (2021-04336) and the Knutand Alice Wallenberg Foundation (grant KAW 2019.0024).

Automation in Air Traffic Control (ATC) is gaining an increasing interest. Possible relevant applications are in automated decision support tools leveraging the performance of the Air Traffic Controller (ATCO) when performing tasks such as Conflict Detection and Resolution (CD & R). Another important area of application is in ATCOs training by aiding instructors to assess the trainees strategies. From this perspective, models that capture the cognitive processes and reveal ATCOs work strategies need to be built. In this work, we investigated a novel approach based on topic modelling to learn controllers work patterns from temporal event sequences obtained by merging eye movement data with data from simulation logs. A comparison of the work phases exhibited by the topic models and the Conflict Life Cycle (CLC) reference model, derived from post-simulation interviews with the ATCOs, indicated that there was a correspondence between the phases captured by the proposed method and the CLC framework. Another contribution of this work is a method to assess similarities between ATCOs work strategies. A first proof-of-concept application targeting the CD & R task is also presented., Funding Agencies|Swedish Transport Administration (Trafikverket); Swedish Research Council [2020-05000]

Denna slutrapport redogör för resultatet av projektet: AutoMon Del I—Automatisk trafikövervakning genom AI i svenska farvatten (TRV2019/95873). Projektägare är Linköpings universitet och genomförts tillsammans med Sjöfartsverket, SAAB, VTI, och Luftfartsverket. Vi kommer i denna rapport redogöra för resultaten samt diskutera framtida utmaningar med konceptet AutoMon. Syftet med AutoMon är att undersöka och belysa problemområdet automatiserad trafikövervakning genom att implementera en AI-demonstrator för svenska farvatten, initialt med fokus på att detektera anomalier i trafiken, och där hanteringen (dvs. granskning och lösning) av problemsituationer lämnas över till en mänsklig operatör. Förekomsten av fartygsolyckor och -incidenter, med potentiellt stora konsekvenser för individ och miljö - utanför etablerade VTS-områden - visar på behovet av utökad övervakning av sjötrafiken i svenska farvatten för att möjliggöra proaktiva åtgärder för att minimera olycksrisker till sjöss. Forskningsprojektet undersöker hur en hög nivå av automation kan användas för att upptäcka och hantera trafikavvikelser på svenskt vatten samt ge möjlighet till s.k. situational awareness (lägesbild) över hela dess yta, samtidigt som stöd för centralt eller distribuerat beslutsfattande ges. Runt om i världen förekommer även manipulation av AIS-systemet och dess positionsangivelser; ett problem som sannolikt kommer att öka även i Sverige. Båda problemställningarna är globala, vilket ger hög relevans. Lösningar har högt värde där digitalisering och artificiell intelligens kan användas som medel för ökad sjösäkerhet (safety och cyber security).

Operational demands in safety-critical systems impose a risk of failure to the operators especially during urgent situations. Operators of safety-critical systems learn to make decisions effectively throughout extensive training programs and many years of experience. In the domain of air traffic control, expensive training with high dropout rates calls for research to enhance novices' ability to detect and resolve conflicts in the airspace. While previous researchers have mostly focused on redesigning training instructions and programs, the current paper explores possible benefits of novel visual representations to improve novices' understanding of the situations as well as their decision-making process. We conduct an experimental evaluation study testing two ecological visual analytics interfaces, developed in a previous study, as support systems to facilitate novice decision-making. The main contribution of this paper is threefold. First, we describe the application of an ecological interface design approach to the development of two visual analytics interfaces. Second, we perform a human-in-the-loop experiment with forty-five novices within a simplified air traffic control simulation environment. Third, by performing an expert-novice comparison we investigate the extent to which effects of the proposed interfaces can be attributed to the subjects' expertise. The results show that the proposed ecological visual analytics interfaces improved novices' understanding of the information about conflicts as well as their problem-solving performance. Further, the results show that the beneficial effects of the proposed interfaces were more attributable to the visual representations than the users' expertise., Funding: KAW Scholar Grant

Operators in air traffic control facing time- and safety-critical situations call for efficient, reliable and robust real-time processing and interpretation of complex data. Automation support tools aid controllers in these processes to prevent separation losses between aircraft. Issues of current support tools include limited what-if and what-else probe functionalities in relation to vertical solutions. This work presents the design and evaluation of two visual analytics interfaces that promote contextual awareness and support what-if and what-else probes in the spatio-temporal domain aiming to improve information integration and support controllers in prioritising conflict resolution. Both interfaces visualize vertical solution spaces against a time-altitude graph. The main contributions of this paper are: (a) the presentation of two interfaces for supporting conflict solving; (b) the novel representation of how vertical information and aircraft rate of climb and descent affect conflicts and (c) an evaluation and comparison of the interfaces with a traditional air traffic control support system. The evaluation study was performed with domain experts to compare the effects of visualization concepts on operator engagement in processing solutions suggested by the tools. Results show that the visualizations support operators ability to understand and resolve conflicts. Based on the results, general design guidelines for time-critical domains are proposed.

In this article, we present a digital platform for unmanned traffic management, UTM City, for research on visualization, simulation, and management of autonomous urban vehicle traffic. Such vehicles orient themselves automatically and provide services ranging from transport to remote presence and surveillance, and new regulations and standards for authorization and monitoring are currently being developed to accommodate for such services. Our system has been developed in close collaboration with domain experts that have contributed with scenarios and participated in numerous workshops to explore the use of visualization in airborne drone traffic monitoring, management, and development of the air space. We share here our experiences with this system and explore the need for visualization in future scenarios to ensure safe, free, and efficient air spaces., Funding Agencies|Swedish Transport Administration; LFV Air Navigation Services of Sweden through the project UTM CITY

Multi Remote Tower Operations (MRTO), where one ATCO has the responsibility of two airports simultaneously, have become an important means to reduce the cost for air traffic control at small regional airports in Sweden without sacrificing safety or service levels. A challenge in MRTO is to keep normal movements operational on an airport while there is busy traffic on the second airport handled by the same ATCO. Earlier work has described the potential of using a digital tower assistant (DiTA), an automation that handles the communication and monitoring of e.g. a single, simple approach and landing on an airport with an otherwise empty sky, while the ATCO needs to focus their attention on the other airport. In this paper we let two interaction designers analyse the interview material from a recent study with five experienced ATCOs, each performing two scenarios using DiTA, and present the conclusions made from an interaction design perspective.