ABSTRACT
The urgency of applying a more ethical approaches to get to a sustainable low-carbon economy by 2050 requires to implement a model of sustainable mobility, which embraces social, economical and industrial activities. In this horizon, behavioral change can produce considerable benefits whose effects are distributed on wider period. In this direction, the GamECAR project aims at provoking a change in driver style towards a more sustainable and efficient use of private cars by applying gamification. However, safety must not be affected by the introduction of new technologies, tools or systems, which are not essential for the driving task. This paper presents a methodology for the control of the inference of a smart-phone application suggesting eco-driving hints to the driver, on the basis of the dynamic assessment of the risk exposure embedded in the current situation. Real-time measurements of physiological, behavioural and car performance parameters are combined with data-driven driver models to determine the safe communication of eco-driving suggestions to the driver. The methodology builds upon the structured approach to operational safety initially applied in aviation and its adaption to the road environment during the XCYCLE Project (Funded by the Horizon 2020 Framework Programme of the European Union – Grant n° 635975).
