ShapeFuture will drive innovation in fundamental Electronic Components and Systems (ECS) that are essential for robust, powerful, fail-operational and integrated perception, cognition, AI-enabled decision making, resilient automation and computing, as well as communications, for highly automated vehicles. Its overarching vision is to bring ECS Innovation at the Heart of Europe's Mobility Transformation, thereby elevating Sovereignty by Perfecting Programmable ECS Solutions for Intelligent, Safe, Connected, and Highly Automated Vehicles. The project will result in the following main tangible outcomes: • Safety, security and reliability of in-vehicle systems to levels appropriate for mass-market deployment. • Availability and supply of leading-edge ECS for the European automotive supply chain and for OEMs to be at the forefront of technology developments in the 2030s. • Increased Accuracy and Robustness of ECS for perception with smaller form factors and lower power consumption. • ECS attributed with cognition features and improved human-Machine Interface (HMI). • ECS with cognitive processing and decision-making capabilities. • ECS for resilient automation and communications. • Increased technology acceptance that will also lead to business sovereignty safeguard. 15 demonstrators and 2 impact studies will showcase the project’s achievements and their capability to deliver innovations and secure future application advances in core markets for European society – Mobility, Green Deal, Digital Society, Safety and Industry. The project innovations will leverage the expertise of world-renowned industrial (5 OEMs, 24 Tier-1, Tier-2 and technology providers) and 12 research partners along the complete automotive and semiconductor value chains, providing Europe with a competitive edge in a growing market. Importantly, ShapeFuture will contribute to ensuring European ECS Sovereignty by shaping the future of ECS in mobility.

The high-performance requirements requested by the industry and consumers are responsible that currently 17% of total plastic packaging is multilayer material , meaning 3.03 Mt of plastics. Difficulties for recycling it are accentuated, being mostly landfilled or incinerated. MERLIN project has joined a partnership between sorting technology providers, recyclers, research centers, social innovation experts and end-users to design cradle to cradle solutions. This 36-month research project will offer innovative solutions for all the processes required to increase the quality and rate of recycled plastic materials coming from multi-layer packaging waste: (i) SORTING (combining optical sensors, Artificial Intelligence (A.I.) and robotics), (ii) DELAMINATION (optimizing depolymerisation and using solvent-based processes), (iii) RECYLING (techniques for repolymerization and upcycling of polymers) and (iv) VALIDATION (developing rigid and flexible packaging solutions and demonstrating circularity of the processes). These solutions will be developed and later validated in a real environment to reach technology readiness level (TRL) 6. This will be complemented with additional techniques and tools for circularity design to increase knowledge and effectiveness in the closure of the European multilayer plastic chain. Finally, transversal activities related to regulation and standardization, safety, sustainability, business, training, dissemination and communication will support to maximize the impact and effectiveness of the project. These actions are aligned with the ones proposed by the European Plastic Strategy to achieve that by 2030 all plastic packaging should be designed to be recyclable or reusable and decrease the quantity of waste generated Potential annual carbon footprint saving that could be achieved recycling all the multilayer waste in Europe could reach 7.42 Mt CO2/year, with a potential economic of €10,605 million and more 106,000 new job positions.

The HAL4SDV proposal aligns with the EU Strategic Research and Innovation Agenda 2022 on Electronic Components and Systems. It aims to pioneer methods, technologies, and processes for series vehicle development beyond 2030, driven by anticipated advancements in microelectronics, communication technology, software engineering, and AI. HAL4SDV envisions a future where vehicles are fully integrated into smart cities, intelligent highways, and cyberspace, blurring the lines between inside and outside the vehicle. Assumptions include data-centricity, code portability, efficient data fusion, unlimited scalability, real-time capabilities, and robust cybersecurity. The objectives encompass unifying software interfaces, creating a hardware abstraction framework, enabling Over-The-Air (OTA) updates, designing platform architectures, ensuring hardware abstraction and virtualization, offering hardware support, automating integration, supporting safety features, harnessing edge computing, implementing security measures, and providing essential development tools. By focusing on these objectives, HAL4SDV aims to establish a unified ecosystem for software-defined vehicles, positioning Europe's automotive industry for continued leadership post-2030 while leveraging existing results and technologies to accelerate progress.

The ambition of PRYSTINE is to strengthen and to extend traditional core competencies of the European industry, research and universities in smart mobility and in particular the electronic component and systems and cyber-physical systems domains. PRYSTINE's target is to realize Fail-operational Urban Surround perceptION (FUSION) which is based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. Therefore, PRYSTINE's high-level goals are: 1. Enhanced reliability and performance, reduced cost and power of FUSION components 2. Dependable embedded control by co-integration of signal processing and AI approaches for FUSION 3. Optimized E/E architecture enabling FUSION-based automated vehicles 4. Fail-operational systems for urban and rural environments based on FUSION PRYSTINE will deliver (a) fail-operational sensor-fusion framework on component level, (b) dependable embedded E/E architectures, and (c) safety compliant integration of Artificial Intelligence (AI) approaches for object recognition, scene understanding, and decision making within automotive applications. The resulting reference FUSION hardware/software architectures and reliable components for autonomous systems will be validated in in 22 industrial demonstrators, such as: 1. Fail-operational autonomous driving platform 2. An electrical and highly automated commercial truck equipped with new FUSION components (such as LiDAR, Radar, camera systems, safety controllers) for advanced perception 3. Highly connected passenger car anticipating traffic situations 4. Sensor fusion in human-machine interfaces for fail-operational control transition in highly automated vehicles PRYSTINE’s well-balanced, value chain oriented consortium, is composed of 60 project partners from 14 different European and non-European countries, including leading automotive OEMs, semiconductor companies, technology partners, and research institutes.

The I-MECH target is to provide augmented intelligence for wide range of cyber-physical systems having actively controlled moving elements, hence support development of smarter mechatronic systems. They face increasing demands on size, motion speed, precision, adaptability, self-diagnostic, connectivity, new cognitive features, etc. Fulfillment of these requirements is essential for building smart, safe and reliable production complexes. This implies completely new demands also on bottom layers of employed motion control system which cannot be routinely handled by available commercial products. On the ground of this, the main mission of this project is to bring novel intelligence into Instrumentation and Control Layers mainly by bridging the gap between latest research results and industrial practice in related model based engineering fields. Next, I-MECH will deliver new interfaces and diagnostic data quality for System Behavior Layer. It strives to provide a cutting edge reference motion control platform for non-standard applications where the control speed, precision, optimal performance, easy reconfigurability and traceability are crucial. The high added value of I-MECH reference platform will be directly verified in high-speed/big CNC machining, additive manufacturing, semicon, high-speed packaging and healthcare robotics. In these sectors, the main project pilots will be validated. However, the platform will be applicable in many other generic motion control fields. The project outputs will impact on the entire value chain of the production automation market and, through envisioned I-MECH center, create sustainable proposition for future smart industry.