Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.

The complexity of in-vehicle interaction systems is constantly growing. However, thanks to the increased availability of sensing systems in the driving environment and communication infrastructure able to radically change the interaction modalities at driving, the existing situation is likely to progressively turn into a cooperative scenario, in which the vehicle and the driver share tasks at perceptual, decisional and control level. This paper describes an innovative human-machine interaction paradigm developed in the SAFE STRIP project to exploit the potential of C-ITS to implement new mobility paradigms, to turn the traditional vehicle perspective into a more efficient traffic perspective. In order to achieve this challenging objective, the overall HMI strategy has been re-designed, to foster the adoption of a new, more active role of the driver and the other road users. The preliminary prototypes developed in the SAFE STRIP project are also described in this paper