This paper surveys artificial intelligence methods for modeling and simulating mixed automated and human traffic, addressing the limitations of existing simulation tools in accurately representing complex driving behaviors. It proposes a comprehensive taxonomy of AI methods, reviews evaluation protocols, and outlines future research directions to bridge the gap between transportation engineering and computer science.