This paper presents a cognitive model designed to reproduce human drivers’ errors in predicting the motion of nearby vulnerable road users. We aim to define a computational model that, given both the trajectory of the eye gaze of a human driver and the trajectory of a bicycle, can compute the probability distribution of where the human driver believes the bicycle will be in the near future. For the design and validation of the proposed cognitive model, we tested 51 subjects in immersive virtual reality scenarios. The results indicate that the proposed model can generate probability distributions of the human drivers’ beliefs about the future bicycle position that are very similar, though not statistically equivalent, to those obtained experimentally. Such models could easily be generalized to describe how drivers misjudge the motion of other road users. This may enable ADAS to evaluate and improve drivers’ situational awareness. In the future, these models could also be used by autonomous cars to evaluate situational awareness of nearby humans, enabling a safer coexistence of autonomous vehicles and vulnerable road users.

Mood and emotion are considered distinct phenomena, yet there is a general lack of consensus within the scientific community concerning their definition. Leveraging on a physiology-based definition of these phenomena and their relation, we propose a concept design to define a real-time realworld positive mood supporting application. In particular, the application will be provided through wearable and portable devices, and comprise different blocks related to the user profiling, the identification of proper mood stimuli based on the users' responses, and a mood detection system. Therefore, multiple data will be exploited to provide an effective and efficient positive mood support, starting from user demographics, moving to an ecological momentary assessment of mood, and integrating physiological signal analyses.

The paper describes the use of interactive Virtual Prototypes (iVP) for the specification of consumer products and for the evaluation of the perceived quality of the product already in its conceptual form. iVPs are based on multimodal interaction including force-feedback and sound in addition to 3D stereoscopic visualization. The fidelity of the prototypes has been evaluated in comparison with the corresponding real products, when used for performing the same tests. Differently from the traditional use of Virtual Prototypes, which aims at evaluating the product design, we have used iVPs for the interaction design of a new product, i.e. it has been used as a means to define the design parameters used for the specification of a new product.