IN2SMART represents the 1st proposal of the Shift2Rail members referred, according to MAAP, to the following Technology Demonstrators (TDs): TD3.7 Railway Information Measuring and Monitoring System (RIMMS), TD3.6 Dynamic Railway Information Management System (DRIMS) and TD3.8 Intelligent Asset Management Strategies (IAMS). These TDs will deploy an overall concept for Intelligent Asset Management based on the following three main interlinked layers: •Measuring and Monitoring systems to collect data from the field related to the railway assets status: IN2SMART will develop unmanned systems for “remote” monitoring; track geometry, switches & crossings and signalling monitoring systems; innovative measurement of train parameters and wheel defects combined with rolling stock identifications systems. •Data management, data mining and data analytics procedures to process data from the field and from other sources: IN2SMART will develop standard open interfaces to access heterogeneous maintenance-related data; analytic tools to automatic detect anomalies, discover and describe maintenance workflow processes and predict railway assets decay towards prescriptive maintenance. •Degradation models and decision making tools to support maintenance strategies and execution: IN2SMART will lay the foundation of a generic framework for asset management and decision support process. This framework will specify the scope, objectives, workflow and outcomes of the decision-making process for maintenance interventions planning, and will be the enabler for the development of future decision support tools and systems. IN2SMART will also develop an optimised tamping tool and a robot platform for maintenance works. IN2SMART will complement the work of the IN2RAIL lighthouse project to reach a homogeneous TRL4/5 demonstrator. The following Grant will start from IN2SMART to reach the final Integrated Technology Demonstrators that will deploy the overall concept of Intelligent Asset Management.

The European railway industry faces great challenges in need for increased network capacity. Ageing infrastructure assets require efficient and sustainable interventions to maintain and improve current levels of performance. To meet these demands and increase the operational performance of the railway infrastructure assets, innovation is needed to enable a step-change in reliability, availability, maintainability and safety (RAMS) and also to optimise asset capital and LCC. The IN2TRACK3 proposal addresses the topic of “Research into optimised and future railway Infrastructure” of the 2020 Horizon 2020 SHIFT2RIL call. The project is a continuation of IN2TRACK and IN2TRACK2 and aims to further develop and demonstrate research results and innovations developed. IN2TRACK3 will develop physical as well as digital technology and methodology demonstrators for the Track, Switches & Crossings and Bridge & Tunnel assets and the project is aligned to the SHIFT2RAIL overall aims. The project structure is designed around three technical sub-projects aiming at both improving the operational performance of existing infrastructure assets and providing radical new system solutions delivering a step-change in performance, improving methods and repair techniques, improve quality, reduce costs and extend the service life of assets and structures. The project is led by Trafikverket, the Swedish Transport Administration Agency, the consortium consists of 27 expert partners originating from 11 European countries and the partners involved are infrastructure managers, research partners, technology developers and industry partners. IN2TRACK3 will further develop and demonstrate a number of innovative solutions based upon the two previous projects and the work will build upon already ongoing mutually beneficial collaboration, established communication paths and a considerable amount of mutual trust built upon years of collaboration in international project environments.

SHOW aims to support the migration path towards affective and persuasive sustainable urban transport, through technical solutions, business models and priority scenarios for impact assessment, by deploying shared, connected, cooperative, electrified fleets of autonomous vehicles in coordinated Public Transport (PT), Demand Responsive Transport (DRT), Mobility as a Service (MaaS) and Logistics as a Service (LaaS) operational chains in real-life urban demonstrations in 5 Mega, 6 Satellite and 3 Follower Pilots taking place in 20 cities across Europe. By deploying a fleet of 74 L4/L5 AVs of all types (buses, shuttles, pods, robo-taxis, automated cars connected with MaaS and cargo vehicles) and for all transport operators (passengers, cargo and mixed transport) in both dedicated lanes and mixed traffic, connected to a wide range of supporting infrastructure (5G, G5, IoT, etc.) and operating under traffic speeds ranging from 18 to over 50km/h, it aims to satisfy 7 UCs families and 22 single UCs; that together cover all urban automated mobility needs and wants of the stakeholders (i.e. as reported within SPACE initiative and in ERTRAC roadmap). Project pilots will last for 24 months, with real service seamless operation in each pilot site lasting at least 12 months and will transport with AV fleets over 1,500,000 passengers and 350,000 units of goods. Being the bigger and more holistic ever real life CCAV urban demonstration initiative, it is user led (by UITP) and realised by a Consortium of 77 Partners, 13 third parties, [terminating 9 partners and 6 third parties] and with the additional support of 60 stakeholders (connected through LoS, including major stakeholder Associations) and twinning actions with 11 organisations the US, S. Korea, Australia, China, Taiwan and Singapore.

Drive2theFuture aims to prepare “drivers”, travelers and vehicle operators of the future to accept and use connected, cooperative and automated transport modes and the industry of these technologies to understand and meet their needs and wants. To achieve this, it models the behaviour of different automated vehicle “drivers” & prognoses acceptance for several automated driving scenarios, develops specialized training tools (3D automated scenarios for VR-goggles, web applications and social media platforms), content, optimized HMI for “driver”-vehicle handovers, CEA and MCA studies for selection of most favorable automated functions realisation and then demonstrates them in 12 Pilots across Europe,and in 3 major events. Pilots cover all automated transportation modes (Automated car, PTW, truck, bus, mini-bus, rail, workboat and drones) and involve driving/riding/rail simulators, VR/AR simulation toolkits, test tracks and real world environments, in which over 1000 AV drivers/passengers, 200 AV operators and 20000 involved citizens experience automation from few hours to 6 months. KPI’s, such as user acceptance, user awareness/appreciation of actual automated function performance (gap between expectations and reality), automated operation efficiency and cost effectiveness, are defined and will be followed through subjective and objective (conflicts analysis) tools. The automated vehicles “driver”/rider/operator behaviour will be modelled and due emphasis is given to cross fertilization issues among different modes. The project will also research relevant legal, ethical and operational issues (with strong user involvement through FIA and 4 of its Clubs, UITP and IRU), the interaction between automated vehicles and relevant MaaS and will issue guidelines, policy recommendations and a user acceptance path Roadmap to Automation. This challenging task is undertaken by 31 Partners from 13 European countries; through 10 interrelated workpackages, over 36 months.