The driving task is highly complex and places considerable perceptual, physical and cognitive demands on the driver. As driving is fundamentally an information processing activity, distracted or impaired drivers have diminished safety margins compared with non-distracted drivers. This competition for sensory and decision making capacities can lead to failures that cost lives. Some groups, teens and elderly drivers for example, have patterns of systematically poor perceptual, physical and cognitive performance while driving. Although there are technologies developed to aid these different drivers, these systems are often misused and underutilised. The DriveID project aims to design and develop a passive, automated face identification system capable of robustly identifying the driver of the vehicle, retrieve a stored profile, and intelligently prescribing specific accident prevention systems and driving environment customizations. (Author/publisher)
Abstract