Theoretically if a human can drive a car using a pair of eyes connected to brain, it should be possible to do that using two cameras connected to some kind of image processing unit.
> Theoretically it should be possible to do that using two cameras connected to some kind of image processing unit
That "some kind of image processing unit" in humans has an awful lot of compute power and software.
If you remove $100k of sensors but have to add $200k of compute to run more advanced computer vision software, then it's a bad tradeoff to use only cameras, even if in theory that software is possible.
In theory. In practice neither the cameras nor processors available in cars function anywhere near human level.
It's not even entirely true in theory. We use a lot of our senses when driving. Force feedback on the wheel. Sounds from the environment. Inertial senses. And our vision isn't fixed, its constantly moving.
And yeah, as you mention, cameras don't really have the same level of range our eyes have and computers don't operate in the same way.
If we want the sell driving computer to be only possibly as good as a human. I can't see in the dark, can't see through fog, and have trouble with rain. Why is human visibility the bar to meet here?
Because we allow humans to drive, therefore if something can perform as well as a human it should be allowed. The bar is a floor, not a ceiling.
Theory isn't really all that applicable to this though - in theory nothing is stopping anyone from writing all code in assembly, but obviously that doesn't happen.
I think more practically cars have adding driver assistance feature for a while now - more cameras, blind spot monitoring, ultrasound for parking, lane drift indicators.
It is therefore not unreasonable to assume that adding more sensors is helpful (but even the old adage of more data is better than less would probably say that).
To be honest, it's possible that having too much data can only cause problems in quick decision-making. Any redundant data will only slow down processing pipelines.
In practice humans aren't particularly safe drivers.
Is that because their vision fails to provide the information necessary to drive safely? Or is it due to distraction and/or poor judgment? I don't actually know the answer to this, but I assume distraction/judgment is a bigger factor.
I'm not a fan of the camera-only approach and think Tesla is making a mistake backing it due to path-dependence, but when we're _only_ talking about this is _broadly theoretical_ terms, I don't think they're wrong. The ideal autonomous driving agent is like a perfect monday morning quarterback who gets to look at every failure and say "see, what you should have done here was..." and it seems like it might well both have enough information and be able too see enough cases to meet some desirable standard of safety. In theory. In practice, maybe they just can't get enough accuracy or something.
> Is that because their vision fails to provide the information necessary to drive safely?
In certain conditions, yes. Humans drive terribly in dark and low light, something lidar excels in.
Still, millions of humans drive every night and only a miniscule percentage cause any accidents. So maybe we are not so bad at this.
According to NHTSA, about half of all fatal crashes occur at night, even though only 25% of driving happens at nighttime. So yes, we are pretty bad at this.
I totally agree, I think most accidents are caused by human nature (especially slow reaction time in specific conditions like being tired or drunk) and ignoring laws of physics (driving too fast). And some are just a pure bad luck (something/someone getting on the road right in front of the car).
Sure, but why strive for that? We can have better than human perception by adding lidar and radar.