Paper Contents
Abstract
Autonomous vehicles (AVs) represent a paradigm shift in transportation, promising safer, more efficient, and convenient mobility. Central to the realization of AVs are advancements in artificial intelligence (AI) technologies, enabling vehicles to perceive their environment, make decisions, and navigate autonomously. This paper examines the multifaceted role of AI in AVs, focusing on the challenges and opportunities it presents. The discussion encompasses the application of AI techniques such as machine learning, computer vision, and sensor fusion in enabling autonomous driving systems. Furthermore, it addresses the technical, regulatory, and ethical challenges associated with AI implementation in AVs, including sensor limitations, data privacy concerns, and legal frameworks. Despite these challenges, AI-enabled AVs offer significant opportunities, including improved road safety, enhanced mobility, and reduced environmental impact. Recent innovations and advancements in AI technologies pave the way for overcoming existing barriers and accelerating the adoption of AVs. Through case studies and real-world applications, this paper highlights the transformative potential of AI-driven AVs across various sectors, from transportation and logistics to urban planning. Looking ahead, future research and development efforts must focus on addressing remaining challenges and maximizing the societal benefits of AI in autonomous vehicles.
Copyright
Copyright © 2024 Sadik Bin Salim . This is an open access article distributed under the Creative Commons Attribution License.
