This is far, far from settled at this point.
In point of fact FSD beta vehicles are out there every day in environments where LIDAR has never been deployed, nor likely ever tested. And we're not seeing clear "it can't do this" failures. Anywhere.
The closest you're going to get to evidence against vision are things like that "It Hit A Kid!" stunt from a few months back that turned out to be basically faked[1].
[1] At least the perps went silent and no one was ever able to reproduce. I mean the whole idea was ridiculous: my car twitches at pedestrians, including kids, including my kids, every day. It literally draws them on the screen.
Do you have evidence of the number of accidents, disengagements etc by region ?
Because you're making awfully definitive statements about FSD safety.
Only if you ignore times where intervention stopped it from hitting something, times where it did actually hit something, massive amounts of jitter and popping in the visual output, phantom braking, etc.
Unless of course "recent" means n+1 where n is the version that crashed into something.
Collision with bollard in Feb 2022: https://www.youtube.com/watch?v=sbSDsbDQjSU
attempts to plow through cyclist Feb 2022: https://www.youtube.com/watch?v=a5wkENwrp_k
almost crashes into tram (can't gauge speed or direction?) Jun 2022: https://www.youtube.com/watch?v=yxX4tDkSc_g
Crashes into curb Aug 2022: https://youtube.com/shorts/8Mh1GjejdsI
Phantom brake Sep 2022: https://www.youtube.com/shorts/5v6j_oL7S-g
Almost colliding with bridge pillar 2 weeks ago: https://www.youtube.com/watch?v=5CMYkDWaqn0
Crashes into various objects in testing 2 weeks ago: https://www.youtube.com/watch?v=yyDxqEzV5Zc
I think your mistake is thinking LiDAR exists to solve the happy day scenario. It doesn't.
Vision is sufficient for the majority of use cases. Where LiDAR comes into its own is in the edge cases because it almost guarantees accurate bounding box detection. Which is where vision is at its weakest.
So I want to know what does FSD do when it sees a billboard of a person or when it is seeing a new object for the first time.
Humans can’t really turn senses off, so they have coffee when driving. Touch and hearing are quite important to “read the road”. Equilibrium too.
All of those are challenging for humans and and probably even more challenging for computer vision with cameras only. But except for the last point, all are obviously improved by lidar.
Is that something the algos can do? Infer the familiarity of the situation?
It should do that in many cases, wet roads, busses with open doors, busses in general maybe, blind corners (does that already to some degree), many people nearby etc.
According to who? Tesla? Because Tesla has a vested interest in trying to prove that they're right even if they're obviously wrong. That's why they constantly try to downplay failures, software issues, device issues etc.
I'm very confused by the attempts to discredit the usefulness of LIDAR. It's another tool you can use to improve the accuracy of your model. Sure, you can use a screwdriver, flip it around and use it as a hammer. But if you need to deal with nails, it's better to grab a hammer instead.
Like there are going to be some environments where Tesla's vision is going to struggle, that's just a fact because you're relying on a more linear set of data. That's why you incorporate as many data points as possible for reasons other commentators have brought up. And I'm confused by how you qualify it as 'working', given we've seen multiple issues which are directly related to their vision approach.
All over this thread you keep making grand statements that “it works”, which is just completely false. It’s simple — if it worked, there would be no driver.
Tesla should probably aim for parking first. Teslas do poorly at self parking:
It's like being driven around by a drunk person - the reaction happens loooooong after the action that causes it has started.
As long as those pedestrians DO NOT actually enter the road after those turns, any "twitching" of your car in response is an ADDITIONAL SAFETY PROBLEM, because other drivers might notice the erratic movements of your car and do erratic things as well, which in the end might result in accidents that wouldn't have happened had your car not "twitched".
Especially "twitchy" AIs like that of your car might very well "re-twitch" on noticing your car doing small, but erratic and rapid changes in behavior, thereby initiating a "twitch escalation spiral".
No, I think this argument is largely correct. And frankly settled: anyone who's driven recent FSD beta versions knows very well that the cars "see just fine". They don't hit anything, they see and avoid obstacles. Frankly they're much more observant than humans are, my car will twitch when pedestrians turn as if they're going to enter the road (where human drivers mostly don't notice, and if they do they ignore it). What problems still exist are in planning: things like sign reading, lane selection, etc... still need some work. But collision avoidance just isn't an issue. It isn't. The LIDAR folks were wrong, basically.
(I will admit though that I'm a little sad about the removal of the ultrasound sensors though. It's true the autonomy probably doesn't need them, but I really like having the chimes to guide parking and garage maneuvering.)