You can build controllable traffic simulators that stay realistic while letting engineers adjust specific behaviors—like making agents safer or faster—without the model gaming the reward system.
This paper presents CNeVA, a framework for creating realistic traffic simulation agents that can both imitate real driving behavior and be steered along interpretable dimensions like speed or safety.