POIs are the content of any application, service, and product even remotely related to our physical surroundings. From navigation applications, to social networks, to tourism, and logistics, we use POIs to search, communicate, decide, and plan our actions. The Big Data assets for POIs and the evolved POI value chain introduced opportunities for growth, but also complexity, intensifying the challenges relating to their quality-assured integration, enrichment, and data sharing. POI data are by nature semantically diverse and spatiotemporally evolving, representing different entities and associations depending on their geographical, temporal, and thematic context. Pioneered by the FP7 project GeoKnow, linked data technologies have been applied to effectively extract the maximum possible value from open, crowdsourced and proprietary Big Data sources. Validated in the domains of tourism and logistics, these technologies have proven their benefit as a cost-effective and scalable foundation for the quality-assured integration, enrichment, and sharing of generic-purpose geospatial data In SLIPO, we argue that linked data technologies can address the limitations, gaps and challenges of the current landscape in integrating, enriching, and sharing POI data. Our goal is to transfer the research output generated by our work in project GeoKnow, to the specific challenge of POI data, introducing validated and cost-effective innovations across their value chain

INFRAMIX, totally aligned with the work programme, is preparing the road infrastructure to support the transition period and the coexistence of conventional and automated vehicles. Its main target is to design, upgrade, adapt and test both physical and digital elements of the road infrastructure, ensuring an uninterrupted, predictable, safe and efficient traffic. To meet this high level objective INFRAMIX is working on different technologies. It starts with the use of mature simulation tools adapted to the peculiarities of automated vehicles and develops new methods for traffic flow modelling, to study the traffic-level influence of different levels of automated vehicles in different penetration rates. It also implements relevant traffic estimation and control algorithms dynamically adapted to the current situation. Then it goes up to propose minimum, targeted and affordable adaptations on elements of the road infrastructure, either physical or digital or a combination of them. This work includes ways of informing all types of vehicles about the control commands issued by the road operator and the proposal of new kind of visual and electronic signals for the needs of mixed scenarios. The outcomes will be assessed via simulation and in real stretches of advanced highways. Key aspects considered throughout the project will be to ensure that the proposed adaptations will not jeopardize safety, quality of service, efficiency and will be appreciated by the users. To achieve its objectives INFRAMIX selects a bottom-up approach. Instead of working in generic solutions with questionable impact, it builds on three specific high value (in terms of importance for traffic efficiency and safety) traffic scenarios, namely “dynamic lane assignment”, “roadworks zones” and “bottlenecks”. Although INFRAMIX is targeting mainly highways (expected to be the initial hosts of such mixed traffic) its key results can be easily transferred to urban roads.

MyCorridor mission is to facilitate sustainable travel in urban and interurban areas and across borders by replacing private vehicle ownership by private vehicle use, as just one element in an integrated/multi-modal MaaS chain, through the provision of an innovative platform, based on mature ITS technology, that will combine connected traffic management and multi modal services and thus facilitate modal shift. It will propose a technological and business MaaS solution, which will cater for interoperability, open data sharing, as well as tackling the legislative, business related and travel-behavior adaptation barriers enabling the emergence of a new business actor across Europe; the one of a Mobility Services Aggregator. MyCorridor will prove this paradigm change through a number of European sites, which are performing long distance and cross border Pilots in a corridor of 6 European countries; from the South (Greece, Italy) through to Central (Austria, Germany, the Netherlands) and Eastern Europe (Czech Republic). Those sites will develop Mobility Package tokens, purchased through one-stop-shop and will incorporate the following services: a) Traffic management services b) Services related to MaaS PT interface c) MaaS vehicle related services and d) Horizontal (business related) services. MyCorridor tasks will be undertaken by a balanced consortium that encompasses all key actors, namely 2 key industrial Partners (SWARCO, Tom-Tom), 7 dynamic SME’s in the mobility market (INFOTRIP, CHAPS, WINGS, MAPTM, AMCO, VivaWallet, HaCon), 1 mobility agency (RSM), 1 ITS association (TTS), 4 Research performers (UNEW, CERTH, UPAT, SRFG), 1 multinational Legal Firm with specialisation in novel mobility scheme structuring (OC) and IRU which will act as the liaison to MaaS Alliance. Also, 11 Letter of Supports have been signed by external to MyCorridor service providers, that commit to allow their services integration in MyCorridor platform.

The assurance of security, privacy, reliability and safety features is key-point to unlock the enormous potential that the connected vehicles systems paradigm i.e., the dynamic Cyberphysical system of highly-equipped infrastructure-connected vehicles with numerous third-party components, can offer towards safer transportation. The emerging systems expose a variety of wireless-communication and hardware interfaces which result in a large attack surface; thus, attempts to assess the degree of confidence that security needs are satisfied come with prohibited cost for automotive stakeholders and OEMs. SAFERtec project will leverage a highly-skilled consortium to first model the varying exposure of a prototype connected vehicle system to numerous threats appearing under two generic instances of the increasingly pervasive V2I setting. One relates to road-side unit communication while the other involves the interaction with cloud application and passengers' smart devices. Then, adopting a systematic vertical approach SAFERtec will obtain an in-depth look of the possible vulnerabilities performing penetration-testing on individual hardware components and upper-layer V2I applications. Considering the available security mechanisms a third party provider already applies to each module, SAFERtec will determine a corresponding protection profile as a summary of the identified risks. An innovative framework appropriately designed for unified and thus, cost-effective use across all modules will employ statistical tools and security metrics to quantify the involved security assurance levels and also feed the incomplete automotive standards. Research on dependability methods will then allow the framework's transition from individual modules to the connected vehicle system. All above results will be incorporated and made available through an open-access toolkit that will pave the way towards the cost-effective identification of security assurance levels for connected vehicle systems.

Big Data integration in European cities is of utmost importance for municipalities and companies to offer effective information services, enable efficient data-driven transportation and mobility, reduce CO2 emissions, assess the efficiency of infrastructure, as well as enhance the quality of life of citizens. At present this integration is substantially limited due to the following factors: 1) Urban Big Data is locked in isolated industrial and public sectors, and 2) The actual Big Data integration is an extremely hard technical problem due to the heterogeneity of data sources, variety of formats, sizes, quality as well as update rates, such that the integration requires significant human intervention. QROWD addresses these challenges by offering methods to perform cross-sectoral streaming Big Data integration including geographic, transport, meteorological, cross domain and news data, while capitalizing on human feedback channels. The main objectives of QROWD are: (1) Facilitating cross-sectoral Big Data stream integration for urban mobility including real-time data on individual and public transportation combined with further available sources, such as weather conditions and infrastructure information to create a comprehensive overview of the city traffic; (2) Supporting participation and feedback of various stakeholder groups to foster data-driven innovation in cities; and (3) Building a platform providing hybrid computational methods relying on efficient algorithms complemented with human computation and feedback. The main outcomes of QROWD are: (1) Two data value chains in the sectors of urban mobility and public transportation using a mix of large scale heterogeneous multilingual datasets; and (2) Cross-sectoral and cross-lingual technology, including algorithms and tools covering all phases of the cross-sectoral Big Data Value Chain building on W3C standards and capitalizing on a flexible and efficient combination of human and machine-based computation.