Self-play has proven to be a highly effective approach for training autonomous driving systems, achieving state-of-the-art performance without using human data. Utilizing the Gigaflow simulator, the study generated an impressive 1.6 billion kilometers of driving scenarios, resulting in a policy that demonstrates exceptional robustness and realism, averaging 17.5 years of continuous driving between incidents in simulation.