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Just for the record though, Musk isn't blindly anti-LIDAR. He has said (and I think this is an objective fact) that all existing roads and driving are based on
by atonse 8mo ago
Just for the record though, Musk isn't blindly anti-LIDAR. He has said (and I think this is an objective fact) that all existing roads and driving are based on vision (which is what all humans do). So that should technically be sufficient. SpaceX uses LIDAR for their docking systems.
I would argue that yes, we do use vision but we get that "lidar depth" from our stereo vision. And that used to be why I thought cameras weren't enough.
But then look at all the work with gaussian splatting (where you can take multiple 2d samples and build a 3d world out of it). So you could probably get 80% there with just that.
The ethos of many Musk companies (you'll hear this from many engineers that work there) is simplify, simplify, simplify. If something isn't needed, take it out. Question everything that might be needed.
To me, LIDAR is just one of those things in that general pattern of "if it isn't absolutely needed, take it out" – and the fact that FSD works so well without it proves that it isn't required. It's probably a nice to have, but maybe not required.
- dymk 8mo agoHumans aren't using only fixed vision for driving. This is such a tiresome thing to see repeated in every discussion about self driving. You're listening to the road and car sounds around you. You're feeling vibration on the road. You're feeling feedback on the steering wheel. You're using a combination of monocular and binocular depth perception - plus, your eyes are not a fixed focal length "cameras". You're moving your head to change the perspective you see the road at. Your inner ear is telling you about your acceleration and orientation.
- kube-system 8mo agoAnd also, even with the suite of sensors that humans have, their vision perception is frequently inadequate and leads to crashes. If vision was good enough, "SMIDSY" wouldn't be such an infamous acronym in vehicle injury cases.
- kelnos 8mo agoFor those of us not aware of Australian cycling jargon, "SMIDSY" means "Sorry, Mate, I Didn't See You".
- anthonypasq 8mo agothe issue is clearly attention not vision when it comes to humans. if we could actually process 100% of the visual information in our field of view, then accidents would probably go down a shit load.
- kube-system 8mo agoHumans have both issues. There are many human failures which are distinctly a vision issue and not attention related, e.g. misestimation of depth/speed, obscured or obstructed vision, optical focus issues, insufficient contrast or exposure, etc.
- arijun 8mo agoBut how many of those crashes not caused by inattention could have been avoided with less idiocy and more defensive driving? I mean, yes, we can’t see as well in fog, but that’s why you should slow down
- kube-system 8mo agoAgain, I'm still not saying that humans don't make bad decisions. I'm saying that, unequivocally, they also get into accidents while paying attention and being careful, as a result of misinterpretation or failure of their senses. These accidents are also common, for example: * someone parking carefully, misjudges depth perception, bumps an object * person driving at night, their eyes failed to perceive a poorly lit feature of the road/markings/obstacles * person driving and suddenly blinded by bright object (the sun, bright lights at night) * person pulling out in traffic who misinterprets their depth perception and therefore misjudges the speed of approaching traffic * people can only focus their eyes at one distance at a time, and it takes time to focus at a different distance. It is neither unsafe nor unexpected for humans to check their instruments while driving -- but it can take the human eye hundreds of milliseconds to focus under normal circumstances -- If you look down, focus, look back up, and focus, as quick as you can at highway speeds, you will have travelled quite a long distance. These type of failures can happen not as a result of poor decision making, but of poor perception.
- saltcured 8mo agoIn theory, a computer should be able to do the same. It could do sensor fusion with even more sense modalities than we have. It could have an array of cameras and potentially out-do our stereo vision, or perhaps even use some lightfield magic to (virtually) analyze the same scene with multiple optical paths. However, there is also a lot of interaction between our perceptual system and cognition. Just for depth perception, we're doing a lot of temporal analysis. We track moving objects and infer distance from assumptions about scale and object permanence. We don't just repeatedly make depth maps from 2D imagery. The brute-force approach is something like training visual language models (VLMs). E.g. you could train on lots of movies and be able to predict "what happens next" in the imaging world. But, compared to LLMs, there is a bigger gap between the model and the application domain with VLMs. It may seem like LLMs are being applied to lots of domains, but most are just tiny variations on the same task of "writing what comes next", which is exactly what they were trained on. Unfortunately, driving is not "painting what comes next" in the same way as all these LLM writing hacks. There is still a big gap between that predictive layer, planning, and executing. Our giant corpus of movies does not really provide the ready-made training data to go after those bigger problems.
- dcrazy 8mo agoPutting your point another way, in order to replicate an average human driver’s competence you would need to make several strong advancements in the state of the art in computer vision _and_ digital optics.
- dzhiurgis 8mo ago20 meters away motion vision is more accurate than stereoscopic vision. What is lidar helping to solve here?
- dymk 8mo agoWaymo claims its system, which uses a combination of LIDAR & vision, resolves objects up to 500 meters away https://waymo.com/blog/2024/08/meet-the-6th-generation-waymo-driver https://waymo.com/blog/2024/08/meet-the-6th-generation-waymo... This company claims their LIDAR works conservatively at 250m, and up to 750m depending on reflectivity https://www.cepton.com/driving-lidar/reading-lidar-specs-part-i-what-they-do-and-dont-tell-you https://www.cepton.com/driving-lidar/reading-lidar-specs-par...
- DesaiAshu 8mo agoIn India (among others), honking is essential to reducing crashes We often greatly underestimate / undervalue the role of our ears relative to vision. As my film director friend says, 80% of the impact in a movie is in the sound
- SOLAR_FIELDS 8mo agoThe day a Waymo can functionally navigate the streets of Mumbai is when we really have achieved l5
- wagwang 8mo agoMost of what you said has nothing to do with lidar vs camera
- dymk 8mo agoWhat I said has to do with "vision only systems" (what Musk has claimed will be enough to do FSD) with sensor fusion systems (what everybody else having success in this space does)
- IncreasePosts 8mo agoI'm positive that Teslas have gyroscopes and accelerometers in them. Our eyes actually have a fairly small focal length range due to the fixed nature of our cornea and only being able to change focal length by flexing the crystalline lens.
- nindalf 8mo ago> So that should technically be sufficient Sufficient to build something close to human performance. But self driving cars will be held to a much higher standard by society. A standard only achievable by having sensors like LiDAR.
- thfuran 8mo agoEven if they weren’t going to be held to a higher standard for widespread acceptance, tens of thousands of people a year in the us die due to humans driving badly. Why would we not try to do better than that?
- sylos 8mo agoBecause that's an acceptable loss and better costs more!
- anthonypasq 8mo agoif a self driving car had the exact vision of humans it would still be better because it has better reaction times. never mind the fact that humans cant actually process all the visual information in our field of view because we dont have the broad attention to be able to do that. its very obvious that you can get super human performance with just cameras. Whether thats worth completely throwing away LiDAR is a different question, but your argument is just obviously false.
- aworks 8mo agoThis reminds me of the time I was distantly following a Waymo car at speed on 101 in Mountain View during rush hour. The Waymo brake lights came on first followed a second or two later by the rest of the traffic.
- hn_acc1 8mo agoBetter reaction times only matter if the decisions are the same / better in every case. Clearly we are not there on that aspect of it yet. Deciding to crash faster, or "tell human to take over" really fast is NOT better.
- stefan_ 8mo agoMentioning gaussian splatting for why we don't need lidar depth is a great example of Musk-esque technobabble; surface level seemingly correct, but nonsense to any practitioner. Because one of the biggest problems of all SfM techniques is that the results are scale ambiguous, so they do not in fact recover that crucial real-world depth measurement you get from lidar. Now you might say "use a depth model to estimate metric depth" and I think if you spend 5 minutes thinking about why a magic math box that pretends to recover real depth from a single 2D image is a very very sketchy proposition when you need it to be correct for emergency braking versus some TikTok bokeh filter you will see that also doesn't get you far.
- servo_sausage 8mo agoThis is not really true if you have multiple cameras with a known baseline, or well known motion characteristics like you get with an accelerometer+ wheel speed.
- anon946 8mo agoSufficient if all else were equal. But the human brain and artificial neural networks are clearly not equal. This is setting aside the whole question of whether we hope to equal human performance or exceed it.
- atonse 8mo agoThat doesn't matter. It's not like we use 100% of our brain capacity for driving. In fact, that's why radio/music/podcasts thrive. Because we're bored when we drive. We have conversations, etc. We daydream. As long as the skills relevant to actually driving are on parity with humans, the rest doesn't matter. In fact, in a recent podcast, Musk mused that you actually may have a limit of how smart you want a vehicle model to be, because what if IT starts to get bored? What will it do? I found that to be an interesting (and amusing) thought exercise.
- BurningFrog 8mo agoTeslas have at least 3 forward facing cameras giving them plenty of depth vision data. They also have several cameras all around providing constant 360° vision.
- pbreit 8mo agoWhy is this getting downvoted? It's good faith and probably more accurate than not.
- thinkcontext 8mo ago> and the fact that FSD works so well without it proves that it isn't required The reports that Tesla submits on Austin Robotaxis include several of them hitting fixed objects. This is the same behavior that has been reported on for prior versions of their software of Teslas not seeing objects, including for the incident for which they had a $250M verdict against them reaffirmed this past week. That this is occurring in an extensively mapped environment and with a safety driver on board leads me to the opposite conclusion that you have reached.
- atultw 8mo agoTo do gaussian splatting anywhere near in real time, you need good depth data to initialize the gaussian positions. This can of course come from monocular depth but then you are back to monocular depth vs lidar.
- maxdo 8mo agoLIDAR also struggle in heavy rain, snow, fog, dust. Check how waymo handle such conditions. It's not only failing, it's causing false positives.