In the last ten years, European Commission has deeply investigated the concern of Powered Two Wheelers (PTW) accidents in the European roads, trying to focus on the improvement of road safety through the introduction of Intelligence Transportation Systems. Several new European research projects involving PTWs have been promoted by EC to resolve this gap: SAFERIDER aiming to enhance rider safety, comfort and, hopefully, reduce fatalities. Four Advanced Riding Assistance Systems (ARAS, or so called in literature ADAS, with Driver instead of Rider) and four In-Vehicle Information Systems (IVIS) will be designed, studied and validated to create a new vehicle concept , with high technical and innovation values. To reach this goal, a priori in-depth accident analyses are performed to discover causes and most common scenarios leading to accidents. Following this, the development of a common architecture able to host ARAS and IVIS is on progress and will be finalized in the next months. To close the loop between vehicle and rider, Human Machine Interface (HMI) concepts are designed and implemented in different ways [1]. A major innovation and breakthrough of the SAFERIDER project, lies with the fact being the first project that considers the integration of several sub-systems on PTWs.

This paper presents the work that has been carried out within the SENSATION Integrated Project [1] concerning the prediction of sleep onset for drivers aiming to provide an effective measure for sleep related accident prevention. Indicators that have been proven to be the most relevant to the physiological manifestation of hypovigilance were examined and exploited in order to develop a holistic physiological sleep predictor that fuses eyelid activity and EEG features. The proposed algorithms were tested using driving simulator data from 35 subjects and the accuracy of the system was measured.

The overall crash statistics in the EU still show a very significant number of car–cyclist crashes. Within the Horizon 2020 project Safe-Up, countermeasures have been developed to reduce this number. One of these countermeasures involves a V2X-enhanced on-board unit for cycles, which can provide on-time warning triggers. The research assumption was based on studying the benefits of connectivity in enhancing cyclists’ safety. This study assessed the performance of this potential technology both qualitatively by analyzing volunteer feedback during physical testing and quantitatively by virtual simulations. The volunteers’ study showed positive findings on system’s safety relevance, user experience, and user acceptance. The method applied for the virtual simulation is a prospective safety performance assessment with reconstructed accident scenarios based on the GIDAS database and cyclist behavior models, obtained from physical testing. The results using a warning trigger 4 s prior to the collision showed a potential safety benefit of approximately 98%. It should be noted that this trigger time was found to be quite early in both physical testing and virtual simulation. Further research is required to evaluate the system’s performance in more complex urban scenarios, as well as to design the human–machine interaction strategies for optimal accident avoidance.