New technologies have allowed pilots to assume more responsibilities reducing the number of some mechanic and repetitive tasks through automation. The flight deck transition to digital computer-based flight management system has shown a reduction of the workload across a variety of tasks. However, there are still several open issues that requires further research and a deeper understanding of pilot cognitive decision making process to guide next steps on aircraft control task sharing between human pilots and machines. Present project proposal will analyse the benefits of cognitive computing assistant and the challenges in key areas such as the relationship between pilot with the surrounding traffic and the aircraft state evolution considering the pressure of the operational context factors such as task responsibilities, situational awareness, and the performance objectives of the mission among others. The dynamics of these interdependencies will be analysed by means of ML techniques identifying the different thresholds that actives a cognitive tasks which will be the baseline to elaborate new symbiosis dynamic structures to improve human-machine information sharing mechanisms. Human-in-the-mesh modelling paradigm relying on cognitive computing technologies will drive the research and innovation efforts to identify the potential changes in pilot roles and task responsibilities that will improve aircraft system reliability and performance, the pathway to automation in the flight deck to simplify the crew interaction with the systems and make tacit knowledge explicit to be accessible and usable for automated, intelligent systems. This proposal consider cockpit operations for “man-computer symbiosis” as a metaphor for designing decision support systems that enhance human cognitive performance. Furthermore, it will be explored the Strong Cognitive Symbiosis approach which analyses true interdependence rather than simply cooperation between human and machines

Europe must seize the opportunities presented by connected, cooperative, and automated mobility (CCAM). For its deployment, powerful tools enabling the design and analysis of CCAM components, digitally and with a common language between TIERs an OEMs are needed. The lack of a validated - and scientifically based - Driver Behavioural Model (DBM) to cover the aspects of human driving performance is one of the main shortcomings of CCAM development. It allows to understand and test the interaction of CCAM with other cars in a safer and predictable way from a human perspective. DBM is the cornerstone for the development of CCAM components. It will guarantee its digital validation and, if incorporated in the ECUs software, will generate a more human-like response of autonomous vehicles (at any level) and increase its acceptance. The main objective of BERTHA is to develop a scalable and probabilistic DBM based mostly on Bayesian Belief Network (BBN). The DBM will be implemented on an open-source, HUB (repository) to validate technological and practical feasibility of the solution with industry and become a unique approach for the model worldwide scalability. The resulting DBM will be translated into a simulating platform, CARLA, using diverse demos which allows building new driving models in the platform. BERTHA will also include a methodology which, due to the HUB, will share the model to the scientific community to ease its growth. The project includes a set of interrelated demonstrators to show this DBM approach as a reference to design human-like, easily predictable and acceptable behaviour of automated driving functions in mixed traffic scenarios. BERTHA is expected to go from a TRL 2 a TRL 4. The requested EU contribution is €7,981,801. The consortium, 14 entities from 6 countries, including South Korea, deem this Project as vitally relevant to the CCAM industry due to its impact for safer and more human-like CAVs and its market and societal adoption.

CommuniCity conducts a large number of innovation pilots in many local communities, both urban, peri-urban and rural, including two EU capitals, aiming to empower hard-to-reach and marginalized communities. It creates three cycles of increasing size, building on two dynamic networks of local administrations and living labs of all sizes. CommuniCity builds on recent highlighted and awarded European as well as national place-based and locally-driven innovation programmes, methods, living labs and platforms. It brings the learnings of these together, and devises an inclusive, community-driven, agile innovation and experimentation model. With this model it runs a large co-creation process, first involving local communities in the challenge definitions, then developing innovative solutions through open calls promoted at the European level as well as locally. It will create new insights into local community innovation processes as well as principles and models of how to scale these insights in inclusive and sustainably manners. In addition, CommuniCity will produce a large number of novel innovations anchored in the needs of the local communities, and an exemplary approach that is followed throughout Europe. The core partner cities are already leading and copied smart communities globally because of their diverse approach and ambition to co-create and share learnings. The same goes for the additional four cities and the two networks. The aim is to push the frontier of community-driven innovation much deeper in society and to the margins of society so that the development and testing of novel innovations better serves the needs of the whole society, based on European values, in the world.

The Ramon Llull-AIRA Postdoctoral Programme (RAMON LLULL) is an international postdoctoral programme offering 33 three-year fellowships to train researchers in the outstanding R&D Institutions in artificial intelligence (AI) in Catalonia to become competent scientific leaders in different scientific disciplines within AI by promoting challenging interdisciplinary R&D projects. The programme is led by the Computer Vision Centre (CVC-CERCA), holder of the current Artificial Intelligence Research Alliance, AIRA, the axis for knowledge generation within the current Catalan Strategy for AI (Catalonia.ai). CVC-CERCA is acting as beneficiary, together with AIRA partner institutions (IIIA-CSIC, BSC, IDEAI-UPC, IRII-CSIC-UPC) and 8 further outstanding research institutions in Artificial Intelligence (AI): UAB, UPF, UdG, URL, URV, Eurecat, i2Cat, IJC-CERCA (5 Universities, 2 Technology Centres and 1 Clinical Research Institution), which will participate as Implementing Partners for the recruitment, hosting & training of the ER fellows. The Programme is created with the explicit encouragement and direct support from the Catalan Government committing to support the activities of the Programme through AIRA Initiative. RAMON LLULL Programme will contribute to boost career perspectives of researchers with outstanding academic quality from a three-dimensional perspective: Excellent Human Centred AI Research; Leadership; and Interdisciplinary Research with other top R&D intensive institutions and companies. The programme will provide a new dimension for the Catalan R&D ecosystem in AI through highly interdisciplinary and intersectoral fundamental research while fulfilling all the principles of Open Science and maintaining the highest research quality standards. It is aimed to optimise the capacity of the Catalan AI ecosystem by recruiting, hosting and training researchers in AI R&I Institutions in Catalonia with the ambition to become competent scientific leaders in different AI disciplines.