AI research has revolutionized automobile
businesses, particularly in self-driving cars. These
autonomous vehicles enhance road safety, transit
efficiency, and individual mobility. AI-powered
applications improve safety standards and enable
autonomous vehicles to assess their surroundings, make
real-time judgments, and operate consistently without
human involvement. The use of AI, machine learning,
deep learning, and neural technologies in driverless
vehicles is expected to increase trust and acceptance. The
study aims to assess advancements and obstacles in AI-
based self-driving cars, focusing on urban planning,
traffic management, and transportation systems.
Further, the research examines autonomous driving
technology, including computer vision, machine learning
algorithms, sensor fusion, and real-time decision-making
systems. It discusses training and learning procedures,
focusing on large datasets, deep neural networks, and
reinforcement learning for improved driving abilities
through continuous interaction with the environment.
Keywords : Artificial Intelligence; transit efficiency; self- driving cars; safety; Technology Development; challenges.