ECE.01R – Distracted Driver Advanced Assistance System

• Talal Ahmed
• Jack Bella
• Abishek Hariharan
• Amir Orman

Distracted driving has become a growing cause of traffic accidents and fatalities. As motor vehicle accidents continue to grow worldwide, the demand for a solution that reduces these accidents has increased. As per the National Highway Traffic Safety Administration, nearly 4000 lives were taken in 2021 due to distracted drivers. Our project aimed to address this pressing issue by developing a device capable of detecting and alerting drivers of distraction. The objective was to create a cost-effective yet efficient system that gave feedback to the driver about their attention through software and hardware peripherals. Our design system included the Jetson Nano, to run our deep learning detection algorithm, along with a camera, accelerometer, and speaker as input and output devices. Our device detected driver distractions through gaze estimation to alert the driver and mitigate the risk of their distraction. The project’s scope was to use existing research on distracted driving as well as using user survey responses to enhance our device. Our system’s goal was to undergo testing to ensure accuracy and reliability for the user within real-world driving scenarios, during these testing phases, we were able to feed our device various data on distracted driving, such as being on your phone and sleeping, to train it to become more accurate over time. In conclusion, our system represents a solution for the critical issue that the world is facing with distracted driving.