Distracted Driver Monitoring System Using AI

Abstract

According to a study, driving while distracted accounted for more than 15% of fatalities in 2008 in the United States. In 65.5% of these cases, the driver was alone in the cab. As all accidents cannot be monitored, the actual number of incidents and fatalities due to driver distraction can be significantly higher than the accounted incidents and fatalities. Some vehicles now come equipped with advanced driver assist systems (ADAS) to provide automated safety. ADAS uses a combination of sensors such as LiDAR, IR cameras, Radar, ultrasonic sensors and Visual spectrum cameras to perform object detection ang get a situational awareness of the vehicle. Based on this, the ADAS system assist the driver or can take emergency action independently to avert a collision. Owing to the cost of ADAS systems, they are available only in premium cars. This paper explored design and development challenges to create an inexpensive, modular solution to monitor driver's and provide an alert when prolonged distraction is detected. This is not a substitute for a commercial ADAS system but a step towards low-cost driver safety options. Because of its modularity and use of commodity-class hardware, the system should be easy to retrofit in any car at an affordable price.