Published Article

ABSTRACT

This study examined the broader advancement of AI and its benefits to robotaxis, a form of fully autonomous vehicles designed to provide ride-hailing services without human drivers. The paper explores the concept of AI, highlighting its ability to simulate human intelligence through machine learning, deep learning, and data-driven decision-making processes. It further analyzes how recent advancements in AI, including generative models and intelligent automation, have enhanced the efficiency, accuracy, and adaptability of autonomous systems. The study also investigates the concept of robotaxis, emphasizing their reliance on advanced technologies such as LiDAR, radar, GPS, and computer vision for real-time navigation and decision-making. Key benefits of AI advancement to robotaxis are identified, including improved road safety, reduction in traffic congestion, increased accessibility, environmental sustainability, and cost efficiency. Additionally, the study highlights other roles of AI in sectors such as healthcare, education, finance, and environmental monitoring, demonstrating its wide-ranging societal impact. Despite these advantages, the paper identifies critical challenges affecting the adoption of robotaxis, including safety concerns, cybersecurity threats, regulatory limitations, ethical dilemmas, and public trust issues. The study concluded by proposing mitigating strategies such as enhancing AI reliability, strengthening cybersecurity systems, developing clear regulatory frameworks, investing in smart infrastructure, and improving public awareness. One of the recommendations made was that developers should invest in advanced machine learning models, real-time data processing, and extensive testing to improve the reliability and safety of autonomous driving systems.