This research aims to explore whether learning and leveraging world models can also be beneficial in visual representation learning for autonomous driving in a closed-loop settings.

This thesis aims to develop a data-driven diffusion model that elevates realism and controllability in simulations and intricately models the complex interactions between multiple agents for safe planning