Integrating Artificial Intelligence in Autonomous Vehicles: Enhancing Safety and Efficiency

Abstract

Autonomous vehicles (AVs) are revolutionizing transportation by integrating artificial intelligence (AI) for enhanced decision-making and navigation. AI driven algorithms, including machine learning and deep learning, enable self driving cars to process real-time data, recognize obstacles, and optimize driving strategies. This paper explores the role of AI in AVs, focusing on sensor fusion, object detection, and trajectory prediction. It examines the impact of AI on reducing human errors, improving road safety, and optimizing traffic management. The study also discusses ethical concerns, cybersecurity threats, and regulatory challenges associated with AI-driven mobility solutions. Future advancements in AI are expected to make AVs safer, more efficient, and widely accepted in global markets.

Keywords: Artificial Intelligence, Autonomous Vehicles, Machine Learning, Safety, Sensor Fusion