You could kickstart training on simulators and then do a transfer, i.e. make adjustments to your final model, on real world data. But to learn only on generated data the problem boils down to the nonparametric features you will be using to state that the generated data is similar to the real data. What is a complex enough feature to say that images are equivalent? They might be statistically equivalent according to your features, but are they really? I think this is a very hard problem, because if we did have a good answer to this question then Tesla & co. would already be training their models on perfect simulators and we wouldn't see the glitches currently found in autonomous driving applications.