The DOMUS project aims to change radically the way in which vehicle passenger compartments and their respective comfort control systems are designed so as to optimise energy use and efficiency while keeping user comfort and safety needs central. Although a more thorough understanding of thermal comfort over recent years has led to significant increases in energy efficiency through better insulation and natural ventilation, substantial room for improvement still exists. With Electric Vehicles (EVs) in particular, which are emerging as the most sustainable option for both satisfying the future mobility needs in Europe and reducing the impact on the environment, inefficiencies must be minimized due to their detrimental effect on the range. Starting with activities to gain a better understanding of comfort, combined with the development of numerical models which represent both the thermal and acoustic characteristics of the passenger compartment, DOMUS aims to create a validated framework for virtual assessment and optimization of the energy used. In parallel, innovative solutions for glazing, seats, insulation and radiant panels, will be developed along with controllers to optimize their performance individually and when operating in combination, the optimal configuration of which will be derived through numerical simulation. The aim is that the combined approach of innovating at a component level together with optimising the overall configuration will deliver at least the targeted 25% improvement in EV range without compromising passenger comfort and safety. Furthermore, the project will demonstrate the key elements of the new approach in a real prototype vehicle. As such DOMUS aims to create a revolutionary approach to the design of vehicles from a user-centric perspective for optimal efficiency, the application of which will be key to increasing range and hence customer acceptance and market penetration of EVs in Europe and around the world in the coming years.

European countries face great challenges because the demographic structure in the EU is changing rapidly, due to reducing birth rates and increasing life expectancies. In 2012, 17% of Europeans were aged 65 and older and in 2020 this will rise to 28%. Meanwhile, the mobility needs of the elderly are also changing. Maintaining a driver's licence is an important issue of independence today, both for males and females. Also technological developments like the introduction of e-bikes enables access to other means of transport. These demographic and behavioural changes are of growing concern to mobility and road safety. While accident data show a decreasing number of fatalities and serious injuries on EU roads, recent data from the ERSO show an increasing proportion of elderly in the fatality statistics. This trend is a serious threat to the achievements of recent decades and poses a challenge that must be addressed to meet goals set for further reduction of road fatalities. Furthermore, there is an increasing rate of obesity in EU populations, which introduces changes in injury patterns and risks. The SENIORS project focuses on the protection of elderly and obese road users also by transferring nowadays younger generations’ safety standards. The objective is to develop the required understanding of accident scenarios, injury mechanisms and risks and to implement these findings in test tools and test and assessment procedures. An integrated approach considering the elderly in multiple transport modes is applied to reduce the portion of elderly fatalities. The small-scale project focuses on providing tools to encourage wider adoption of advanced restraint and pedestrian protection systems improving the protection of older and obese vulnerable road users. The activities consolidate results from previous EU projects such as THORAX and AsPeCSS and meet the needs defined by the GRSP IWG on Frontal Impact working on a near-term (2015) and mid-term (2020) update of UN-R94.

The vision of NexaSphere is to create a system capable of facilitating a 3D network of networks. This framework seamlessly integrates multi-path transmission to enhance multi-connectivity in an energy-saving manner, bringing together spaceborne and airborne platforms with terrestrial infrastructure. The main goal is to deliver societal benefits to the future European landscape, with a particular focus on mobile transportation (including air mobility, railway, and automotive sectors), smart cities, and communities beyond the year 2030. NexaSphere's primary objective is to conceptualize and develop advanced hardware prototypes and software algorithms for a sustainable multi-connected 3D network. This network will integrate radio and wireless-optical technologies, and enabling network orchestration through AI-driven programmability. Additionally, NexaSphere aims to extend the edge-cloud continuum into space, creating a Radio & Wireless-Optical Connectivity Continuum from short-range to long-range. By integrating scalable simulation models in a hardware-in-the-loop approach and conducting in-lab and relevant environment validation, NexaSphere seeks to demonstrate proof-of-concept for this TN/NTN unified network architecture, targeting a Technology Readiness Level (TRL) of 4-5. These demonstrations will showcase the benefits of the proposed architecture, particularly within the mobile transportation sector, covering aeronautics, railway, and automotive industries.

The metrology domain (which could be considered as the ‘eyes and ears’ for both R&D&I and production) is a key enabler for productivity enhancements in many industries across the electronic components and system (ECS) value chain and have to be an integral part of any Cyber Physical Systems (CPS) which consist of metrology equipment, virtual metrology or Industrial internet of things (IIoT) sensors, edge and high-performance computing (HPC). The requirements from the metrology is to support ALL process steps toward the final product. However, for any given ECS technology, there is a significant trade-off between the metrology sensitivity, precision and accuracy to its productivity. MADEin4 address this deficiency by focusing on two productivity boosters which are independent from the sensitivity, precision and accuracy requirements: • Productivity booster 1: High throughput, next generation metrology and inspection tools development for the nanoelectronics industry (all nodes down to 5nm). This booster will be developed by the metrology equipment’s manufacturers and demonstrated in an industry 4.0 pilot line at imec and address the ECS equipment, materials and manufacturing major challenges (MASP Chapter 15, major challenges 1 – 3). • Productivity booster 2: CPS development which combines Machine Learning (ML) of design (EDA) and metrology data for predictive diagnostics of the process and tools performances predictive diagnostics of the process and tools performances (predictive yield and tools performance). This booster will be developed and demonstrated in an industry 4.0 pilot line at imec, for the 5nm node, by the EDA, computing and metrology partners (MASP Chapter 15, major challenge 4). The same CPS concept will be demonstrated for the ‘digital industries’ two major challenges of the nanoelectronics (all nodes down to 5nm) and automotive end user’s partners (MASP Chapter 9, major challenges 1and 3).

Problem: Automated transport technology is developing rapidly for all transport modes, with huge safety potential. However, the transition to full automation brings new risks, such as misuse, overreliance, reduced situational awareness and mode confusion. The driving task changes to a more supervisory role, reducing the task load and potentially leading to degraded performance. Similarly, the automated system may not (yet) function in all situations; it must intelligently assess the strengths and weaknesses of both driver and system and select the best control mode according to the context. Solution: MEDIATOR proposes an intelligent ‘mediating’ support system for road transport, enabling safe, real-time switching between human driver and system. It will constantly evaluate driving context, driver state and vehicle automation status, personalising its technology to the driver’s general competence. Approach: MEDIATOR pursues a paradigm shift away from a view that prioritises either the driver or the automation, instead integrating the best of both. It will use state-of-the-art knowledge, including that from other transport modes, and develop new knowledge about human behaviour and human-machine interaction. It will apply the latest artificial intelligence technology to evaluate driver state, automation status and driving context in real time. It will produce several prototypes in the lab and in actual vehicles, for evaluation in simulation, simulator and on-road studies—as well as several tools for further exploitation. Impact: MEDIATOR will optimise the safety potential of vehicle automation, especially during the transition to full automation. It will reduce future as well as current risks (such as inattention or fatigue). MEDIATOR will facilitate market exploitation by actively involving the automotive industry during the development process. Further, the involvement of experts from other transport modes will maximise the transfer of knowledge to these domains.