The data and experience gathered from real-world testing should (I'm not saying "will") accelerate the progress to the point you mention - "once their error rate drops below that of a human driver".
Let's look at the Uber case, since everyone infers so much from it. One fatality. One. And the program was immediately shut down. And how did it happen? Engineers had deliberately disabled the automated emergency braking system to reduce "erratic behavior", but had no automated notification to the driver. And the driver was distracted, doing data entry for the test as he was instructed to do. If the emergency braking system had been on, it would have stopped the car on time - they have the data for this.
This sure looks like human error to me.
And that single accident put Uber's program drastically behind schedule, relative to more cautious/thorough competitors. Uber paid a market price for its eager carelessness.
We don't have reason to believe that. Even Uber now agrees that more simulation should have been done, and they're trying to catch up. All the necessary data for this could have been gleaned from instrumenting human-driven cars, and then testing the object recognition, object avoidance, and other driving algorithms against the resulting data.
Uber's Arizona death wasn't "human error". It was negligence. They also weren't "behind schedule" in any meaningful sense; some exec picked a too-aggressive goal, and people cut corners in a vain attempt to meet it. They shouldn't just be paying a "market price". They should be facing charges for criminal negligence leading to involuntary manslaughter.
If Uber was more focused on doing things the right way their program would be much further ahead.
Aren't self driving error rates already below human drivers? The fatality rate is extremely skewed by one incident in which the system detected an obstacle but wasn't allowed to stop the car because it was disabled (so... not a failure of the self driving aspect of that system) and another in which a partial self driving system warned a driver repeatedly to take the wheel, but they did not.
In both instances the problem was a failure to force action by the human drivers (or failed reliance on them). In the former case, the system would have braked, in the second, the system should brake instead of asking for help from the driver.
Meanwhile the overall crash rate for self-driving cars is lower, correct?
I don't think that's correct in general, and especially not so if you compare the conditions that each are driven under. Said a bit differently, the human error rate is in all conditions (rain / snow / nighttime / unmarked roads / gravel) where most self-driving miles are on well-marked city and highway roads in near ideal conditions.
But you're already no-true-scotsmanning your way to giving the self-driving cars unrealistically good scores. Yes, a cause behind the Uber crash is indeed Uber disabling a safety system they thought unnecessary. But we have no reason to believe some other companies aren't also either turning off or just never adding safety systems.
My objection is not to better testing. It's to bad comparisons. Including, as here, with somebody handwaving at data that, at best, couldn't answer the question.
But since you aren't, I'm guessing even you don't really believe what you're saying. Which is good, because a key assumption of your theory is proven wrong by the article you're commenting on.
Yes, these vehicles will eventually save lives once their error rate drops below that of a human driver. But there's no reason to think that running over a bunch of real people is necessary for progress until these cars work well in simulations. As the article explains, they get orders of magnitude more testing done in simulation than on the road.
Uber's rush to test things in the real world was not about advancing the technology or saving lives. It was about getting a short-term commercial advantage on the cheap.