With one finger typing on the phone, apologies CJ, I'm going to comment here
Some of what you ask, depending obviously on mapping (V1) or programming (V2), they could be aware of / count / negotiate to passing places better than most human drivers.
There are several videos on the page, one shows it meeting and dealing with an oncoming car. I don't know whether there was any 'negotiation' . However, the article talks about AI learning. How, I have no idea, but that knowledge is then available across the fleet and could continue throughout the vehicle's life.
One potential issue with (re narrow lanes) AVs is that they can be too accurate with steering, potentially focusing wear of the road surface. And the sensor systems and the vehicle's 'awareness' of its size and position will, again, probably be far better than most drivers. Self-park has been available for years. But they may be unable to determine whether there's an overgrown bush to brush past, or a solid wall to barge into.
However, I've seen (early last year) a demonstration of a video analytics system that - then - could identify 1000 different items. As a f'rinstance, heading into The Mall in London, it not only identified (placing a bounding box on screen) usual stuff such as pedestrians, cyclists, cars, bollards, traffic lights - but also (identified and boxed separately) a horse and rider.
Re emergency vehicles, many already have GPS location live to control rooms, wifi hotspots, livestream video capabilities. Only a small step to broadcast location and direction to the EV and 'arrange' a clear path through.
None of this will happen overnight, or anytime soon. That's an understatement
But - despite the hype, smoke and mirrors, missed deadlines - the progress in systems development has really been quite incredible.
PS Did anyone notice the car breaking a couple of laws?