Published Article

ABSTRACT

This study examined the role of artificial intelligence (AI) and robotics in improving autonomous driving systems for safer and more dependable transportation. The study explained how AI enables machines and autonomous vehicles to think, learn, analyse data, and make intelligent decisions through technologies such as machine learning, deep learning, sensors, cameras, radar, LiDAR, and real-time data processing systems. The study further discussed robotics as an interdisciplinary field that combines mechanical engineering, electrical engineering, computer science, and AI to develop intelligent machines capable of sensing their environment and performing automated driving operations with little or no human assistance. Autonomous vehicles were identified as advanced transportation systems designed to reduce human driving errors, improve traffic management, enhance road safety, and increase transportation efficiency. The study also highlighted important strategies for leveling up AI in autonomous driving, including improving machine learning and deep learning models, enhancing sensor fusion and real-time data processing, and strengthening cyber security and data protection systems against cyber threats and unauthorized access. Despite challenges such as public trust, ethical concerns, infrastructure limitations, and legal issues, continuous advancements in AI and robotics continue to promote the development of safer, smarter, and more reliable autonomous driving systems capable of transforming modern transportation in the future. The study concluded that artificial intelligence (AI) and robotics have greatly improved autonomous driving by making vehicles safer, smarter, and more reliable. The study recommended that governments and transportation agencies should invest in smart road infrastructure and digital traffic systems to support the effective operation of autonomous vehicles.