[njoubert]

That's not quite right. There are learned models inside the planning systems of most of the sophisticated self-driving car companies. Here's a public video that gives a few high-level examples: https://vimeo.com/618478174

Full disclosure, I work for Aurora in the Planning group.

[Jensson]

How do you know those models are safe? I know Google said they didn't use machine learning for the driving part.

Edit: To clarify, I wonder how you do this part:

> make safe, predictable decisions on the road.

ML models doesn't make predictable outputs. So you always need a system that can handle the ML model going haywire, since you have no way to prove that it wont.

[AlotOfReading]

This is probably a miscommunication issue. Waymo absolutely uses machine learning in the perception and prediction layers of the stack. Underneath that are a few layers of trajectory planning and controls code that don't necessarily need ML.

As for stack accuracy and predictability, they're active areas of research for everyone, and part of the secret sauce. There's lots of little mitigations scattered throughout everyone's stacks for various particular issues, but no silver bullet.