Authors: Mayuri R. Tone, Mohammad Abdul Razzaq, Syed Abdur Rasheed, Saud Ahamed
Abstract: Artificial Intelligence (AI) has become the cornerstone of autonomous vehicle (AV) technology, enabling self-driving systems to make complex, real-time decisions with minimal human intervention. By integrating machine learning, deep neural networks, computer vision, and sensor fusion, AI allows vehicles to interpret their surroundings, predict potential hazards, and plan safe and efficient routes. Decision-making in AVs relies on continuous data analysis from LiDAR, radar, cameras, and GPS to assess dynamic traffic conditions and respond adaptively to unpredictable environments. AI algorithms learn from vast datasets to improve accuracy, reliability, and safety, ensuring context-aware and ethical decision processes. This paper explores the pivotal role of AI in enhancing the perception, reasoning, and decision-making capabilities of autonomous vehicles, highlighting current advancements, challenges, and the potential impact of intelligent systems on the future of transportation.
