Proven positive effects of Cooperative Intelligent Transport Systems (C-ITS) are in many cases prohibited by the non-negligible cost required for the initial installation but also maintenance of the infrastructure and the on-board vehicle intelligent systems that need to be deployed for their operation. In parallel, a series of State of the Art cooperative safety and automated solutions do not exploit data directly originating from the infrastructure and the environment, failing, in this way, to have the most reliable possible safety critical information that is vital to the optimum fulfillment of their objectives; that being primarily the increase of traffic safety. SAFE STRIP (SAFE and green Sensor Technologies for self-explaining and forgiving Road Interactive aPplications) EU funded project envisions to simultaneously address those challenges by introducing a revolutionary C-ITS approach through the placement of low-cost innovative sensorial frameworks on the road pavement surface itself in order to acquire reliable and lane specific traffic and environmental information that is directed through I2X (Infrastructure to Everything) communication to all types of vehicles. The current manuscript presents the vision and objectives, the core use cases serving as the proof of concept of the technological solution built, the implementation approach towards delivering the solution and, finally, the multilayered validation approach anticipated by the Consortium towards delivering a prototype of an as much as possible high technological readiness as well as C-ITS functions evidencing its value.

Preventive safety functions help drivers avoid or mitigate accidents. No quantitative methods have been available to evaluate the safety impact of these systems. This paper describes a framework for the assessment of preventive and active safety functions, which integrates procedures for technical performance, human factors, and safety assessments in one holistic approach. The concept of situational control , which is defined as the degree of control that a joint driver–vehicle system exerts over a traffic situation, has been introduced. Assessment involves technical evaluation , which assesses that the system and all subsystems work according to the functional and technical specifications, human factors evaluation, which assesses the behavioral situational control parameters, and safety potential evaluation, which performs a detailed assessment of internal and external impact mechanisms that change the situational control at the traffic level. The methodology has been applied to the INSAFES project, which integrates lateral and longitudinal control functions.

The profound, pervasive and enduring consequences of ageing population present enormous challenges as well as enormous opportunities for Information and Communication Technology. The EU funded OASIS project, a Large Scale Integrated Project, is aimed to develop an open and innovative reference architecture, based upon ontologies and semantic services, that will allow plug and play and cost-effective interconnection of existing and new services in all domains required for the independent and autonomous living of the elderly and their enhanced quality of life. Among other technological advances, in OASIS we are developing a smart multisensorial platform for monitoring the lower limbs movements, as well as the muscular activations. We are using unobtrusive integrated sensors to transduce posture and kinematic variables and to acquire surface Electromiography (sEMG). The platform is able to analyze and merge the sEMG signals and kinematics variables to provide a single coherent dynamic information of the acquired movements. A Predictive Dynamic Model (PDM) based on machine learning techniques assesses the physiological muscular recruitments as well as muscular fatigue and physiological conditions.