(untitled) (Journal of Artificial Intelligence Research, 2023)
Autonomous driving technology has witnessed remarkable advancements in recent years, largely due to the integration of machine learning (ML) techniques. This paper provides a comprehensive overview of ML applications in autonomous driving systems, focusing on perception and decision-making aspects. It discusses how ML models improve perception tasks such as object detection and tracking, as well as decision-making processes like path planning and traffic prediction. The paper also examines challenges and future directions in the integration of ML algorithms for achieving safer and more efficient autonomous vehicles.