5 ms·
I can't understand why instead of using all the possible senses: vision, auditory, radar, lidar they want to only use vision as if there's some sense of "purity
by gerash 5y ago
I can't understand why instead of using all the possible senses: vision, auditory, radar, lidar they want to only use vision as if there's some sense of "purity" in doing that.
- soperj 5y agoIt's entirely cost.
- stevenpetryk 5y agoI mean, it's gotta be style and complexity too. LIDAR are quite ugly on test vehicles. Cameras are much simpler and easier to hide among the body.
- rcMgD2BwE72F 5y agoBecause Tesla lacks money? Their automotive gross margin is 28% (Toyota is at 17.76%). If one automaker could afford LIDAR, it's Tesla.
- soperj 5y agoLIDAR has come down a lot in cost over the last decade, but it would still eat up that whole 28% and more.
- nr2x 5y agoPure cost cutting at expense of safety certainly.
- jliptzin 5y agoHumans do fine with only 2 cameras
- HoDaMoFoDor 5y agoHumans also have GI.
- nr2x 5y ago…and yet…
- givinguflac 5y ago*And a brain that outclasses anything Tesla could currently put into their vehicles by numerous orders of magnitude.
- zamalek 5y agoIn addition to the sibling comments, humans are also terrible drivers. They almost universally confuse confidence with ability.
- nr2x 5y agoHm, almost like tech CEOs.
- dreamcompiler 5y agoChimpanzees have the same number of cameras as humans. Yet we don't let them drive. It's a puzzler. /s
- rcMgD2BwE72F 5y agoSo they could put PS5-level gaming rigs in their cars? How logical https://www.theverge.com/2021/6/1/22462660/amd-tesla-model-x-s-plaid-ryzen-radeon-rdna-2 https://www.theverge.com/2021/6/1/22462660/amd-tesla-model-x...
- nr2x 5y agoOh you’re right, I didn’t realize they are investing in safety features like putting gaming consoles in car dashboards. That will save millions of lives. All Hail Elon.
- LeoPanthera 5y agoWhich of the above would solve this problem?
- mtalantikite 5y agoI'm not an expert, but I'm guessing Tesla's version of lidar wouldn't detect the moon. It's probably a bit out of range.
- rcMgD2BwE72F 5y agoAnd when the moon shows up next to a pole, a bridge or any high up structure, the car comes to a stop because it "sensed" something. You must solve vision anyway, so why use a crutch?
- deleted 5y ago[deleted]
- gerash 5y agoLidar could make this false prediction less likely. That said, the computer vision is still far from human level. It lacks a common sense around how the world works.
- deleted 5y ago[deleted]
- cogman10 5y agoLIDAR. You'd be able to tell there's no object anywhere near the car and disregard the light.
- rcMgD2BwE72F 5y agoUnless it's hanging from a cable https://www.masterfile.com/image/en/700-08743685 https://www.masterfile.com/image/en/700-08743685. But then, it could be a streetlight so only vision can solve this problem https://www.123rf.com/photo_2753272_hanging-street-lamp.html https://www.123rf.com/photo_2753272_hanging-street-lamp.html
- extropy 5y agoUsing all the senses would not solve the problem. Vision is the only one with enough resolution to matter. That said: - way cheaper - more reliable - less power hungry - simpler and easier to debug.
- njarboe 5y agoI think one of the main reasons for Tesla to use only vision is that then the mistakes the system makes will be more understandable and thus acceptable to humans. The way radar and lidar systems fail and cause wrecks will seem strange to humans, like running into stationary objects. Even if using these sensors would make system better overall, they might not be worth including if one is shooting for human acceptance of the system as fit for use. An autocar seeing something that looks like a red light and breaking (or breaking for a bit and then continuing after deciding it was not a red light) is going to be acceptable to people because that is how they behave. Phantom breaking due to some radar or lidar input that the human can't perceive is going to be interpreted very negatively. I imaging auditory might be added at some point, if it is not already being used.
- bathtub365 5y agoI find the mistakes it makes to be less understandable because I can see with my eyes that the light in the sky is the moon, and not a traffic light. Why can’t the car?
- jillesvangurp 5y agoThree reasons: 1) They have hundreds of millions of cars sold already with cameras that they can up-sell this to. That means more revenue. But more importantly, more training data. Massive amounts of it. Training data is the real value here. Radar/lidar/etc. might be able to detect better what is obvious to a human just looking at a thing. But given enough training data, a machine learning can probably replicate that capability so you don't actually need the fancy sensors. Adding new sensors to the mix would set them back quite a while on that front. 2) Simplicity. More sensors means more complexity integrating all the signals and gathering the right training data. More failure modes, etc. It probably also means more compute power needed to process all that data. More complex testing, etc. Scaling by keeping the sensor platform simple is a good move here. 3) The hard part of autonomous driving is actually interpreting visual signals in complex or unusual/rare situations. Roads are designed for humans with eyes. Lidar sees a blob, radar detects a pole, a camera sees a traffic sign, road markings that mean something, etc. It's a much richer signal. All the important stuff on roads is clearly visible. So, cameras are far more important for this than lidar/radar. Those are really great for avoiding crashing into things. Not so much for interpreting and classifying those things. And Tesla seems to be doing pretty OK with not crashing into things. Mostly, the amusing edge cases have to do with misinterpreting visual signals for which radar and lidar are probably not that relevant. It's an interesting approach that they clearly believe that they can make work. It does not actually stop them from later adding more hardware to enhance things if they decide those things are needed. But it's quite interesting how far they are getting with just cameras.
- stonewareslord 5y agoFor #1: wouldn't more sensors be even better for training? If vision does not pick up an object like a human, but lidar detects a human sized object, the vision portion of the model can 'learn' from it's mistakes. The other two sound like good reasons though
- jillesvangurp 5y agoExcept that would kind of invalidate all the training data they've gathered for the last years which does not have data for these sensors. That would be a major setback and might take years to fix. Probably they started ignoring the radar sensor content quite some time ago when they realized they did not need it. They never had any lidar. Obstacle detection with lidar/radar is only interesting if you assume that object avoidance is a problem with camera based obstacle detection right now. There are lots of incidents with Teslas but I don't recall them running over pedestrians or crashing into vehicles a lot. Mostly incidents are about misinterpreting visual signals; not about crashing into stuff. If anything, their safety statistics are pretty good when autopilot is on. The cars still do dangerous/illegal/misguided things due to misinterpreting of traffic situations but it's then smart enough to get the driver out of trouble before bad things happen.