Authors : Dr. T. Amalraj Victoire; Dr.A.Karunamurthy; S.Sathish; R.Sriram

Volume/Issue : Volume 8 - 2023, Issue 7 - July

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/2fs56utv

DOI : https://doi.org/10.5281/zenodo.8142415

Abstract : 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.