Distracted Driver Detection System Using Deep Learning Technique
Improvement of public safety and reducing accidents are the intelligent system's critical goals for detecting drivers' fatigue and distracted behavior during the driving project. The essential factors in accidents are driver fatigue and monotony, especially on rural roads. Such distracted behavior of the driver reduces their thinking ability for that particular instant. Because of this loss in decision-making ability, they lose control of their vehicle. Studies tell that usually the driver gets tired after an hour of driving. Driver fatigue and drowsiness happens much more in the afternoon, early hours, after eating lunch, and at midnight. These losses of consciousness could also be because of drinking alcohol, drug addiction, etc. The distracted driver detection system proposed in this chapter takes a multi-faceted approach by monitoring driver actions and fatigue levels. The proposed activity monitor achieves an accuracy of 86.3%. The fatigue monitor has been developed and tuned to work well in real-life scenarios.