There is no particular reason why advanced planning, modelling and pattern matching ability should need human-like goals.
Heck, even counting votes would be quite impossible (how much divergence does a copy need before it gets its own vote? What it not all modules/nodes are copied?).
Also, the anti-suffrage women seem to have been erased from history as far as popular discourse goes... guess the Women's National Anti-Suffrage League isn't taught in schools (support amongst women for extending the vote was very lukewarm, becoming a majority only after the law changed).
Because driving requires the ability to understand what other drivers are doing. It requires a theory of mind, which means understanding human goals.
I think instead of flirting with this absurd fantasy of self-driving cars we should be doing more to invest in railroads and other forms of mass transit so that people don't need to drive at all. Europe and Asia are far ahead of North America in this regard.
I'm a transit advocate, but there are some fundamental issues that need to be resolved first, especially in North America.
Of course it is trivially true that we all intend to go from point A to B. But that is almost irrelevant. It is the million micro-decisions on the trip that count.
Without seeing the human, I assess in seconds whether the other driver is unusually high or low-skills, focused or distracted or impaired, polite or rude... and this constant assessment, with human understanding, of (others') human goals and attitudes is a key element of driving skills, and yes this is basically all covered in your exception of needing to account for stupidity of people. That exception is just bigger than you think.
Like chess?
Chess is really just about searching through as much of the space as possible, and you can take a few seconds. And believe me, there's a whole lot more stupid behaviours you can encounter on the road while you have to react in less than a second.
That isn't really an accurate description of how the modern DL bots work. They don't need to reference any database of past games while they play.
As an experiment, try making a chess AI without explicitly giving it the rules of the game and see how it performs.
This reminds me of the kinds of intuitions people had about Chess and Go. In retrospect they seem silly, but it made plenty of sense to them at the time. The fact was that there was a solution that machines could use that humans couldn't use. Naturally, a solution that humans couldn't use was hard for them to anticipate being effective.
Single-track railroad like in airport terminal-to-terminal transport? Fine.
Out on the open rail network? Not even close. And that is a LOT more constrained & predictable than an open road network.
Getting to all cars being software-driven seems as much in the near-mid future as was the idea of having full vehicle-to-vehicle telemetry &communications - i.e., sounded like a great idea until it crashed on the rocks of practicality (and inter-corporate politics?); not likely happening in a relevant time frame.