Artificial Intelligence (AI) contributes significantly to the development of autonomous vehicles in an unmatched way. This paper outlines techniques and algorithms for the implementation of Intelligent Autonomous vehicles (IAV) leveraging AI algorithms for traffic perception, decision-making and control in autonomous vehicles through merging traffic scenario detection, traffic lane detection, semantic segmentation, pedestrian detection, and traffic sign classification and detection. The modern computer vision and deep neural networks-based algorithms enable the real-time analysis of different vehicle data through artificial intelligence. The vehicle dynamics are constituted through AI in vehicle control systems for increased safety and efficiency to ensure that they are optimized with time. In addition, the paper will also discuss challenges and possible future directions, underscore how AI has the potential of driving autonomous vehicles towards safer and more reliable as well as intelligent transportation systems. This is the hope of the future whereby mobility is intelligent, sustainable, and accessible with the combination of AI with autonomous vehicles.