Driver Behavior Recognition using Machine Learning

Abstract

Driver behavior recognition plays a crucial role in reducing the risk of traffic accidents. Most existing methods for monitoring drivers rely heavily on computer vision techniques. However, such approaches often raise concerns related to privacy and the possibility of spoofing. In this study, we propose a novel and effective deep learning-based approach for analyzing driver behavior. The method focuses on cues such as facial expressions to accurately identify and understand the driver’s state. The results indicate that the proposed technique is capable of reliably detecting driver behaviors. we study convolutional neural networks(CNNs)from photographs built from manipulated alerts based on the circular plot technique. As a result, it changed into confirmed that the proposed technique can detect the driver’s behavior.