Artificial Intelligence for Autonomous Vehicles

9Models for the Driver Assistance System

B. Shanthini¹*, K. Cornelius¹, M. Charumathy¹, Lekshmy P.², P. Kavitha³ and T. Sethukarasi³

¹St. Peter’s Institute of Higher Education and Research, Tamil Nadu, India

²LBS Institute of Technology for Women, Tamil Nadu, India

³RMK Engineering College, Tamil Nadu, India

Abstract

Road traffic collisions are one of the leading causes of death and injury in our society; as a result, they are a significant contributor to the loss of both human lives and financial goods. The vast majority of accidents are brought on by human mistake, such as a lack of attention, being interrupted, being sleepy, having insufficient preparation, and so on; these errors lead to catastrophic bodily injuries, fatalities, and large financial losses. Driver assistance systems (DASs) have the potential to reduce the number of mistakes that are made by humans by monitoring the conditions of the road and alerting the driver of an impending danger by issuing a number of recommendations, suggestions, and alerts. Because drivers being distracted is one of the leading causes of traffic collisions, this is something that has to be done. Sluggishness location is the goal of this research, which will accomplish this goal with the assistance of data on the eye state, head posture, and mouth state of the driver. This will be done in order to improve the quality of the information that was gathered in the first place, which was received from the public drowsy driver data bank. ...