Generative artificial intelligence for intelligent transportation systems: Bridging real-world innovations and classroom learning [Essay]

Generative artificial intelligence (AI) is fundamentally reshaping intelligent transportation systems (ITSs), moving beyond traditional optimization to create synthetic data, simulate complex scenarios, and draft adaptive policies. However, the rapid evolution of these tools creates a widening gap between static classroom theory and dynamic professional practice. This article explores how generative AI serves as a bridge, transforming engineering education through a “prompt–simulate–critique” framework. Drawing from a senior-level course, we outline five key thrusts, ranging from foundational data analytics and automated mobility to societal ethics and sustainability, where tools like large language models (LLMs) and generative adversarial networks (GANs) are integrated into the curriculum.