Real-Time AI-Enhanced Driver Monitoring Systems
Abstract
Driver distraction and fatigue have become major concerns for road transport authorities worldwide. Fatigued and distracted drivers' reaction times are delayed, they have decreased sensory perceptions, and their decision-making abilities are affected. They have an increased risk of being involved in a road accident, which can cause property damage and personal injury as well as fatalities. From 2019 to 2020, there was an increase in deaths on Australian roads of 3.8%, and fatalities involving heavy vehicles increased by 4.5%. A proposed increase in heavy vehicle accidents in New South Wales may not be a surprise given the percentage of all commuter travel that heavy vehicles represent. It is thus most important to design and implement an accurate driver monitoring system that can detect inattentive, distracted, and fatigued drivers as quickly and correctly as possible. While significant expertise currently resides within specialist personnel, the research now seeks to provide those analysts with an AI-enhanced driver monitoring system, presenting a live real-time video summarizing any instances of the driver being inattentive, fatigued, or tired.
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