2020

Davoli, Luca; Martalò, Marco; Cilfone, Antonio; Belli, Laura; Ferrari, Gianluigi; Presta, Roberta; Montanari, Roberto; Mengoni, Maura; Giraldi, Luca; Amparore, Elvio G.; Botta, Marco; Drago, Idilio; Carbonara, Giuseppe; Castellano, Andrea; Plomp, Johan

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.