Abstract: This paper explores how Reinforcement Learning (RL) can be a valuable tool for enhancing decision-making in autonomous driving systems when integrated with autonomous vehicle control. Stakeholders in the autonomous driving industry share a sense of both anticipation and necessity when it comes to incorporating RL into self-driving technologies. In this examination of RL applied to autonomous driving, we delve into the comparative analysis of various RL-driven applications within the context of autonomous vehicle control.

Keywords: Autonomous Driving, Reinforcement Learning, Self Driving Cars, Vehicle Control, Traffic Management, Traffic Optimization.

| DOI: 10.17148/IARJSET.2024.11709