Implementing a Gaze Tracking Algorithm for Improving Advanced Driver Assistance Systems

Car accidents are one of the top ten causes death and produced mainly by driver distractions. ADAS (Advanced Driver Assistance Systems) can warn dangerous scenarios, improving road safety, reducing number traffic accidents. However, having a system that is continuously sounding alarms be overwhelming or confusing both, counterproductive. Using driver’s attention to build an efficient main contribution this work. To obtain “attention value” use Gaze tracking proposed. Driver’s gaze direction crucial factor in understanding fatal distractions, as well discerning when it necessary about risks on road. In paper, real-time proposed part development obtains communicates information. The developed uses information determine if drivers looking with their full attention. This work gives step ahead based driver, building warns only case distraction. was implemented model-based using Kinect v2.0 sensor adjusted set-up environment tested suitable-features driving simulation environment. average obtained results promising, hit ratios between 96.37% 81.84%.