Right now, car AI has trouble both with kids and non-white persons. That said, when it comes to the things it is good at detecting, the cars respond much more quickly. This came up when an official asked about how it detects brake lights, and the project advisor (from Google, I think) explained that the car doesn't worry about break lights but instantly detects when a car ahead of it rapidly decelerates, and responds immediately.

I'm pretty sure we can get cars smart enough and sharp enough to drive better than humans. But the recent incident in San Francisco where Cruise driverless taxis blocked an ambulance with a patient in critical condition (resulting in their death), suggests to me we underestimated the layers of logistics necessary to make cars truly autonomous.

Randal Munroe listed a few more incidents we can expect (Obligatory XKCD).

According to other commentors, the need will never arise because the AI cars will be programmed so well it's impossible to have accidents 🙄... now I see why FSD will never become a reality.

Good question. Neural networks are modelled after how brains learn and process information, so it's certainly theoretically possible for a neural network (or other machine learning algorithm) to make inferences like that, just like how you've learned them with years of experience.

The biggest challenge in any machine learning is finding enough labelled training data. In fact, a friend of mine contributed to a paper in which (no joke) GTA V was used to generate labelled training data for an automous vehicle. Because it's a game engine, every object in the game is already digitized, and the 3D modelling is accurate enough to be useful, at least. This vehicle used LIDAR so the actual shaders and such didn't matter as much as the 3D point cloud.