Revolutionizing Roads: Exploring Self-Driving Cars Through Cutting-Edge CNN Techniques

Abstract

This research investigates the integration of cutting-edge Convolutional Neural Network (CNN) techniques to enhance the capabilities of self-driving cars. By leveraging advancements in object detection, real-time processing, and adaptability, we aim to revolutionize autonomous transportation. Through a thorough literature survey encompassing seminal works in autonomous vehicles and CNN applications, this study pioneers a comprehensive exploration. Comparative analyses and ethical considerations provide a holistic understanding of the transformative potential of CNNs in shaping a safer and more efficient future for our roadways. The findings presented contribute to the ongoing evolution of self-driving technologies, marking a significant stride towards a revolutionized era in transportation.