AN EXPERIMENT TO DETECT AND REDUCE DISTRACTED DRIVING

Over the years, distracted driving has been primarily responsible for the increase in road accidents. Nearly 330,000 accidents caused each year are due to texting while driving. Some of the other reasons leading to fatal crashes are intoxication, sleeplessness, and rash driving. 

This paper describes an experiment designed to mitigate distracted driving and create a safe and accident-free environment. Considering that the pose of a human head is a crucial visual cue to determine driver-focus, human intention, motivation, etc., in this experiment the position of the driver’s head and eyes are captured and classified by the visual recognition technology, Deep Convolution Neural Network (DCNN).

The experiment not only uses DCNN but also a collective approach which includes DCNN, Computer Vision (C.V), and Principal Component Analysis (PCA).

In the automotive industry, pioneering product development and ongoing commitment to innovation is a sure-shot formula for success. So, did this experiment incorporating new disruptive technologies help in preventing drivers from being distracted or reduce road accidents? 

Download this white paper and find out now! 
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