Autonomous Vehicles and Intelligent Decision-Making Systems: A Review

Abstract

Autonomous vehicles (AVs) represent one of the most transformative advancements in modern transportation systems, integrating artificial intelligence (AI), machine learning (ML), sensor fusion, and real-time data analytics to enable self-driving capabilities. Intelligent decision-making systems form the cognitive backbone of AVs, allowing them to perceive environments, interpret complex scenarios, predict dynamic behaviors, and execute safe navigation strategies without human intervention. This review paper critically examines the evolution, architecture, methodologies, and challenges of autonomous vehicles with a focus on intelligent decision-making frameworks.