I agree with the objective stated in the article; that people really do need to be much better educated about what semi-self-driving cars
can't do. Sadly, the video fails to accomplish that task. The video says the car doesn't have time to stop after it "sees" the dummy car parked in its lane.
This is simply wrong. It's not that the car doesn't have time to stop, it's that
The car is not engineered to stop for stationary obstacles. I see a lot of disbelief in comments from people when this is pointed out. What, semi-self-driving cars (including those under the control of Tesla Autopilot + AutoSteer) don't even
try to see large stationary objects in the car's lane? Unbelievable, they say!
The problem is two-fold:
1. Automatic braking systems depend on Doppler radar. That only detects relative differences in speed. Anything that's stationary (relative to the unmoving background) is ignored. It
has to be ignored if it's not moving. If a system dependent on Doppler radar to sense things didn't ignore the background, then it would constantly be detecting things everywhere which needed to be braked for -- false positives everywhere -- and the car would never go anywhere!
2. Tesla cars use video cameras and optical object recognition software to "see" things such as other vehicles and obstacles in the vehicle's path. Unfortunately, that software is so unreliable about placing obstacles that it "sees" that Tesla couldn't possibly rely on it. In a
promo video that Tesla put out in Nov 2016, we see literally hundreds of objects being "painted" by Autopilot as "in-path" objects, even when they are stationary objects well to the side of the road -- including hundreds of trees! This is again a case of an overwhelming number of false positives. Obviously if Autopilot stopped the car every time it detected such an object, then -- again -- the car would never go anywhere.
Of course, we can hope Tesla has improved the software somewhat since then, but -- based on what I know about the history of robotic R&D and the fallibility of optical object recognition software -- I think it's extremely unlkely that this can be improved, over the next few or several years, to the point that it will be reliable enough for human lives to depend on it. If roboticists have not been able to make truly reliable optical object recognition software despite working hard on the problem for decades, then it's very unlikely Tesla is going to solve that problem within the next few years.
In my opinion, self-driving cars, or even reliably operating semi-self-driving cars, are going to have to have better sensors --
much better sensors -- than the low-res Doppler radar units which all cars with ABS systems are using. They need sensors which actively "ping" the environment to get a positive signal return, rather than relying on passive sensors such as video cameras.
In other words, they need active scanning with lidar or a high-res radar array, or both.