  In the burgeoning field of intelligent transportation systems, the
integration of Generative Artificial Intelligence (AI) into vehicular networks
presents a transformative potential for the automotive industry. This paper
explores the innovative applications of generative AI in enhancing
communication protocols, optimizing traffic management, and bolstering security
frameworks within vehicular networks. By examining current technologies and
recent advancements, we identify key challenges such as scalability, real-time
data processing, and security vulnerabilities that come with AI integration.
Additionally, we propose novel applications and methodologies that leverage
generative AI to simulate complex network scenarios, generate adaptive
communication schemes, and enhance predictive capabilities for traffic
conditions. This study not only reviews the state of the art but also
highlights significant opportunities where generative AI can lead to
groundbreaking improvements in vehicular network efficiency and safety. Through
this comprehensive exploration, our findings aim to guide future research
directions and foster a deeper understanding of generative AI's role in the
next generation of vehicular technologies.
