It also simplifies the stack a lot to have a single set of sensors, so the software becomes mostly: getting good training data (iterative loops from failing production cases) and an efficient training algorithm.
This scales to more than just AD and also can leverage new breakthroughs from academia
No, humans do significant sensor fusion.
There's binaural audio: useful to detect and have a rough position of emergency services and/or high speeds cars(it's true that its a relatively unencumbered channel, but that makes it all the more valuables for emergencies)
And there's a working if imperfect IMU (performance can be altered if the power supply is set to an alternate mode) to sense all kinds of acceleration: for fine course correction on acceleration and bearing, for getting the road condition and adjust the driving profile accordingly, etc..
I don't doubt that it's possible with machine vision alone, but it makes the challenge substantially harder.