Ai-Driven Autonomous Driving Systems: Advancements, Architecture, Challenges, and Future Trends in Intelligent Transportation Technologies

Abstract

Artificial Intelligence (AI) has revolutionized the landscape of modern transportation, leading to the emergence of autonomous driving systems that promise safer, smarter, and more efficient mobility solutions. The integration of AI with advanced sensors, machine learning algorithms, and decision-making models has enabled vehicles to perceive, interpret, and react to complex driving environments without human intervention. This paper explores the architecture, components, and functioning of AI-driven autonomous driving systems, discusses recent technological advancements, identifies key challenges in their deployment, and highlights potential future trends. The research emphasizes how AI-based perception, path planning, and control systems contribute to realtime decision-making, safety optimization, and sustainable mobility.

KEYWORDS: Artificial Intelligence, Autonomous Vehicles, Deep Learning, Sensor Fusion, Intelligent Transportation, Machine Learning, Path Planning, Safety Systems, Smart Mobility, Computer Vision.