Leveraging Reinforcement Learning for Enhancing Autonomous Driving Systems

Abstract

This paper explores the application of Reinforcement Learning (RL) techniques in the development of autonomous driving systems. It reviews the fundamental principles of RL, discusses its integration into autonomous vehicle systems, and evaluates the advantages and challenges of employing RL in this domain. By analyzing recent advancements and case studies, this paper aims to provide a comprehensive overview of how RL can improve decision-making and driving performance in autonomous vehicles.