The project has the objective to industrialize an innovative, flexible and cost-effective dynamic road sign system as a valid alternative to the actual static road sign infrastructure on expressways. The problem: Road signs in motorways sometimes do not reflect road conditions or properly inform drivers due to their static nature. In particular speed limits and road works signs often change due to different conditions and need to be replaced manually. This exposes road maintenance personnel to dangerous works and results in higher life-cost cycle per sign. The solution: An innovative low-cost, low-power, low-maintenance, and highly flexible “variable message road sign” based on paper-display technology and centrally controlled has been designed and prototyped that demonstrate less life-cycle costs and higher flexibility. Road Builders and maintenance authorities as well as system integrators for road infrastructures are a Potential Market. Preliminary assessments have been conducted that indicate a great potential of the innovation. The business potential of the solution could also extend to other markets (such as digital out of home) but the project will concentrate to transportation to maximize the probability of success of the initiative. The business approach. Customers have already been approached and more will be approached directly or via stakeholders and business partners from the actual portfolio of the proponents. Dissemination and marketing promotion will be carried out to achieve a critical mass of interested customers for the industrialization phase. Feasibility will also target pilot deployment with interested customers. Objective of the feasibility study is to provide the basis for the solution and the business approach minimizing the risks for the proponents and the early adopters in the industrialization phase while augmenting the competitive advantage.

The objective of the I-ALLOW project is therefore to study, design, develop and test an innovative approach which improves the safety of population and infrastructure in day time, night time and all-weather conditions by proving a state of the art multi-spectral imaging and processing system. I-ALLOW will be able to: • A low cost single sensor imaging solution with versatile capabilities. • Image in low light (night-time) conditions. • Image in standard light (day-time) conditions. • Image in harsh weather conditions (rain, snow, smog). • Object detection based on multispectral data. • Object detection based on 3D range data.

The REXASI-PRO project aims to release a novel engineering framework. The REXASI-PRO project aims to release a novel engineering framework to develop greener and Trustworthy Artificial Intelligence solutions. In the methodology, safety, security, and explainability are entangled. In addition, throughout the entire lifecycle of the framework, ethics aspects will be continuously monitored. To this end, the REXASI-PRO project introduces several novelties. The project will develop in parallel the design of novel trustworthy-by-construction solutions for social navigations and a methodology to certify the robustness of AI-based autonomous vehicles for people with reduced mobility. The trustworthy-by-construction social navigation algorithms will exploit mathematical models of social robots. The robots will be trained by using both implicit and explicit communication. REXASI-PRO methodology augments existing system-level and item-level engineering frameworks by leveraging novel eXplainability methods to improve the entire system's robustness. REXASIPRO will release additional verification and validation approaches for safety and security with the AI in the loop. Among the other developments, a novel learning paradigm embeds safety requirements in Deep Neural Network for planning algorithms, runtime monitoring based on conformal prediction regions, trustable sensing, and secure communication. The methodology will be used to certify the robustness of both autonomous wheelchairs and flying robots. The flying robots will be equipped with unbiased machine learning solutions for people detection that will be reliable also in an emergency. Thus, REXASI-PRO will make the AI solutions greener. To this end, both an AI-based orchestrator to augment the intelligence of the robots and topological methods will be developed. The REXASI-PRO framework will be demonstrated by enabling the collaboration among autonomous wheelchairs and flying robots to help people with reduced mobility.

Despite technological breakthroughs in connected and automated transport, the total transformation of existing transportation into a fully autonomous system is still decades away. In the meantime, mixed traffic environments with semi-autonomous vehicles proactively passing the dynamic driving task back to the human driver, whenever system limits are approached, is expected to become the norm. Such a Request to Intervene (RtI) can only be successful and met with trust by end-users if the driver state is continuously monitored and his/her availability properly evaluated and sufficiently triggered (through tailored human-machine interfaces - HMIs). In parallel, driver training has to evolve to account for the safe and sensible usage of semi-automated driving, whereas driver intervention performance has to be made an integral part of both driver and technology assessment. Besides, the ethical implications of automated decision-making need to be properly assessed, giving rise to novel risk and liability analysis models. The vision of Trustonomy (a neologism from the combination of trust + autonomy) is to maximise the safety, trust and acceptance of automated vehicles by helping to address the aforementioned technical and non-technical challenges through a well-integrated and inter-disciplinary approach, bringing domain experts and ordinary citizens to work closely together. Trustonomy will investigate, setup, test and comparatively assess, in terms of performance, ethics, acceptability and trust, different relevant technologies and approaches, including driver state monitoring systems, HMI designs, risk models, and driver training methods. This will be done through both simulator and field based studies, in a variety of autonomous driving and RtI scenarios, covering different types of users (in terms of age, gender, driving experience, etc.), road transport modes (private cars, trucks, buses), levels of automation (L3 - L5) and driving conditions.

Ensuring public spaces safety while preserving the freedom of citizens represents a challenge for European societies. Soft targets like malls, stadiums or big events continue to face a variety of evolving cyber and physical threats. To secure public spaces and other soft targets requires an integral security approach and new concepts involving all the security actors along with private operators. APPRAISE aims to build on the latest advances in big data analysis, artificial intelligence, and advanced visualisation to create an integral security framework that will improve both the cyber/physical security and safety of public spaces by enabling a proactive, integrated, risk-based, and resilience-oriented approach. This framework will be designed to support the secured private-public collaboration and optimise the coordination of operations involving private security staff, private operators, and law enforcement agencies. APPRAISE will offer unprecedented capabilities to predict and identify criminal and terrorist acts and enhance the operational collaboration of security actors before, during, and after an incident occurs. Social, Ethical, Legal, and Privacy observatories bringing together LEAs, private operators, technology experts, psychologists, sociologists, and society representatives will ensure full conformity of the developed tools with current EU legislation and citizens’ acceptance, preparing the ground for successful exploitation. The consortium consists of world-class research centres, industries, SMEs, LEAs of different types (national police, municipal police, elite tactical unit) as well as private security practitioners and operators, coordinated by a large industrial company with a leading position in the security market. APPRAISE will demonstrate its solutions in four complementary pilot sites: a tennis tournament in Italy, a transnational cycling tour with stages in France and Spain, an international fair in Poland, and a mall in Slovenia.