Argue the case for modular perception-prediction-planning versus end-to-end learned driving, then say what you would actually build.

Start by defining the mechanism in the prompt, its assumptions, and the quantities it changes. Then connect those mechanics to model quality, optimization behavior, compute or memory cost, and the main failure mode.

Use equations or tensor shapes where they clarify the claim, then name an experiment or ablation that would distinguish competing explanations.