Road accidents continue to be a major public safety concern. Human error is the main cause of accidents. Intelligent driver systems that can monitor the driver’s state and behaviour show promise for our collective safety. VI-DAS will progress the design of next-gen 720° connected ADAS (scene analysis, driver status). Advances in sensors, data fusion, machine learning and user feedback provide the capability to better understand driver, vehicle and scene context, facilitating a significant step along the road towards truly semi-autonomous vehicles. On this path there is a need to design vehicle automation that can gracefully hand-over and back to the driver. VI-DAS advances in computer vision and machine learning will introduce non-invasive, vision-based sensing capabilities to vehicles and enable contextual driver behaviour modelling. The technologies will be based on inexpensive and ubiquitous sensors, primarily cameras. Predictions on outcomes in a scene will be created to determine the best reaction to feed to a personalised HMI component that proposes optimal behaviour for safety, efficiency and comfort. VI-DAS will employ a cloud platform to improve ADAS sensor and algorithm design and to store and analyse data at a large scale, thus enabling the exploitation of vehicle connectivity and cooperative systems. VI-DAS will address human error analysis by the study of real accidents in order to understand patterns and consequences as an input to the technologies. VI-DAS will also address legal, liability and emerging ethical aspects because with such technology comes new risks, and justifiable public concern. The insurance industry will be key in the adoption of next generation ADAS and Autonomous Vehicles and a stakeholder in reaching L3. VI-DAS is positioned ideally at the point in the automotive value chain where Europe is both dominant and in which value can be added. The project will contribute to reducing accidents, economic growth and continued innovation.

Although previous EU funded projects have defined tools and concepts to ensure safety of nano-enabled products through design, many hurdles still hinder the implementation of these procedures in real production processes. ASINA will use the production value chains (VCs) of two representative categories of nano-enabled products (NEPs): coatings in environmental (clean) nanotechnology and nano-encapsulating systems in cosmetics, to formulate design hypothesis and make design decisions by applying a data-driven approach and methodology (the “ASINA-SMM”). Molded on industrial six sigma practices, the ASINA-SMM can be easily adopted by manufactures to deliver NEPs designed to be as safe as possible, so achieving ASINA vision to increase stakeholders (entrepreneurs, scientists, regulators, innovators, policy makers, consumers) confidence in SbD nanomanufacturing. The methodology encompasses distinct phases that ASINA will follow to deliver SbD solutions and supporting tools, at TRL6: define NEP, its intended use, production technologies and known quality, safety and cost requirements; measure performance attributes (techno-economic features, hazard and exposure potential along the entire life cycle) in relation to material (M) and process (P) design options; analyse data gathered from internal and external sources and derive/combine response functions, to identify the best compromise between possible design options; design new versions of the product/process that minimise risk, maximising performance; establish a pilot action to verify the capacity of ASINA-SMM to deliver practical, relevant, reliable and reproducible M- or P-SbD solutions. By its end, ASINA will provide a roadmap to generalise ASINA-SMM, and maximizing the positive impacts of further products, designed to improve environmental quality and human health/wellness, offering the transparency required to promote consumer acceptance and, as a consequence, the growth of reference industrial sectors.

Engineered nanomaterials (ENMs) are covered by REACH/CLP regulations; the general opinion is that the risk assessment (RA) approach routinely used for conventional chemicals is also applicable to ENMs. However, as acknowledged by OECD and ECHA, the OECD and ISO Test Guidelines (TGs) and Standard Operating Procedures (SOPs) need to be verified and adapted to be applicable to ENMs. RiskGONE will support the standardization and validation process for ENM by evaluating, optimizing and pre-validating SOPs and TGs and integrating them into a framework for risk governance (RG) of ENMs. The framework will comprise modular tools and will rely heavily on current strategies for the RA of conventional chemicals, complemented by methods for estimating environmental, social and economic benefits. It will incorporate ethical aspects and societal risk perception and will manage acceptable and unacceptable risks through transfer or mitigation. The focus of RiskGONE will be to produce nano-specific draft guidance documents for application to ENM RA; or, alternatively, to suggest ameliorations to OECD, ECHA, and ISO/CEN SOPs or guidelines. Rather than producing assays and methods ex novo, this will be achieved through Round Robin exercises and multimodal testing of OECD TGs and ECHA methods supporting the “Malta-project”, and on methods not yet considered by OECD. This process will be accelerated by guidance documents for data storage/curation/accessibility optimisation, applied to well-characterized reference ENMs typifying the main physicochemical and toxicological features of ENMs. The conditions for a transparent and self-sustained organisational form for science-based RG, representing EU stakeholders, member states, industry and civil society, will be established. The RG framework and methods developed by RiskGONE will be transferred to the organisational form for RG.

The main objective of NANORIGO (NANOtechnology RIsk GOvernance) is to develop and implement a transparent, transdisciplinary and science-based Risk Governance Framework (RGF) for managing nanotechnology risks regarding social, environmental and economic benefits. A new risk management approach is formed based on available and new high-quality data and advanced scientific tools developed for industry and regulators decision-making, and on communication with all stakeholders (regulators, industries, politicians, the civil society). The RGF will use a life-cycle perspective and integrate available knowledge on ethical, social, environmental and economic concerns into a user-friendly format that can be easily adapted and transferred into regulation for hazard, exposure and risk assessment and management of nanomaterials. It will consist of: (i) risk management strategies based on reinforced tools for guidance and decision-making developed for risk assessment, (ii) validated methodologies to identify potential hazard and exposure, and (iii) a web-based information and communication platform to facilitate access to good quality data and a clear understanding of risks for all stakeholders, and their valuable feedback. The NANORIGO work plan consists of 8 work packages covering all major risk governance aspects. A self-sustained European Nanotechnology Risk Governance Council (NRGC) will be installed to implement the RGF, embedded in relevant international structures and in close cooperation with the International Risk Governance Center (IRGC). Case studies will demonstrate the sustainability of solutions and their consistent integration into regulatory applications under real conditions. Bringing all stakeholders together under a common umbrella will allow to share and integrate the most appropriate governance tools, frameworks and plans for future science and regulatory research and foster consistency of management approaches in the EU and synergies internationally.