this post was submitted on 02 Nov 2024
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You are making it far simpler than it actually is. Recognizing what a thing is is the essential first problem. Is that a child, a ball, a goose, a pothole, or a shadow that the cameras see? It would be absurd and an absolute show stopper if the car stopped for dark shadows.
We take for granted the vast amount that the human brain does in this problem space. The system has to identify and categorize what it's seeing, otherwise it's useless.
That leads to my actual opinion on the technology, which is that it's going to be nearly impossible to have fully autonomous cars on roads as we know them. It's fine if everything is normal, which is most of the time. But software can't recognize and correctly react to the thousands of novel situations that can happen.
They should be automating trains instead. (Oh wait, we pretty much did that already.)
That's why they use LIDAR and not just visual cameras. They don't need to know the difference between different objects; they just need to know an object is there, in the way, or even moving in a way that could potentially put it in the path of the vehicle.
They're making it more complicated by working on both autonomous driving, and also image recognition for use by AI.
I agree that LIDAR or radar are better solutions than image recognition. I mean, that's literally what those technologies are for.
But even then, that's not enough. LIDAR/radar can't help it identify its lane in inclement weather, drive well on gravel, and so on. These are the kinds of problems where automakers severely downplay the difficulty of the problem and just how much a human driver does.
It isn't a matter of which is better - you use both, and more.