I work on full-3D simulations (using a game engine) for an autonomous car company. I can't speak for every AV company, but in my experience, simulators are used far more for testing than 'training'. The appeal of using a 3D game engine for simulation is that you can create inputs to the car's perception system. Without this ability, you're stuck either replaying recorded data, or spoofing out perception and only testing planning/controls and down. These two approaches are actually extremely powerful, so the vast majority of AV simulation testing is not done in full 3D.

There are some situations where 3D simulation is useful, though. First, it allows you to run your AV software in its entirety (i.e., not spoofing perception), making for a very complete integration test. A 3D sim can capture complex, interesting occlusions that other sims cannot. Another fairly common use case is experimenting with new sensor setups before they're added to the car.

As for training, it's mostly research at this point. I think there's promise in using synthetic data to supplement real-world data training data for perception systems.

There are a number of companies trying to market simulation 'platforms' to AV makers. I think there's the potential for one of these products to gain traction -- but it's a difficult sell. AVs are enormously complicated, a 3rd party product would need to both beat in-house sims and support a lot of very specific (and likely propriety) AV features.