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Why Tesla removed radar and ultrasonic sensors [video]

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Re: Why Tesla removed radar and ultrasonic sensors [video]

#391

Post by tsimionescu »

Reason077 wrote: post #385
tsimionescu wrote: post #283

Earlier quoted context omitted.

The optical sensors are just a small part of the human (and animal in general) vision system. A much bigger component is our innate (evolutionarily acquired) understanding of basic mechanics, simple agent theory, and object recognition. When we look at the road, we recognize stuff in the images we get as objects, and then most of the work is done by us applying basic logic in terms of those objects - that car is off…

> "A much bigger component is our innate (evolutionarily acquired) understanding of basic mechanics, simple agent theory, and object recognition. ... they are interpreting the image at a slightly higher level of abstraction by applying some assumptions and heuristics that evolution has "found"." Of course, and all this is exactly what self-driving AIs are attempting to implement. Things like object recognition and un…

Putting all of these together amounts to building AGI. While I do believe that we will have that one day, I have a very hard time imagining as the quickest path to self-driving.

Basically my contention is that vision-only is being touted as the more focused path to self-driving, when in fact vision-only clearly requires a big portion at least of an AGI. I think it's pretty clear this currently means this is not a realistic path to self-driving, while other paths to self-driving using more specialized sensors seem more likely to bear fruit in the near term.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#392

Post by kwhitefoot »

somat wrote: post #363
YZF wrote: post #233

Earlier quoted context omitted.

A car typically doesn't have lights shining in all directions. My Tesla doesn't at an rate. At night, backing into my driveway, I can barely see anything on the back-up camera unless the brake lights come on. If it's raining heavily it's much worse. But the ultrasonic sensors are really good at detecting obstacles pretty much all around.

Just curious, do teslas have a reverse light?

Yes. Only one on my 2015 Model S 70D. Not sure how many on other Teslas.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#394

Post by P_I_Staker »

jandrese wrote: post #129
petilon wrote: post #33

I didn't find his answers particularly convincing. His answer focused on costs mainly, and how "the best part is no part". We have already seen multiple accidents caused by camera's limitations [1] which would not have happened if Tesla used Lidars. Cameras have poor dynamic range and can be easily blinded by bright surfaces. While it is true that humans do fine with only eyes, our eyes are significantly better than…

> While it is true that humans do fine with only eyes We do not. Humans are terrible at driving. Traffic accidents are one of the leading causes of death in the developed world. Billions of dollars of property damage occur every year because humans are not up to the task. A self driving system that is as safe as an average human driver would be an absolute failure.

We are excellent at driving. It's shocking that there aren't more accidents.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#395

Post by hammock »

CharlesW wrote: post #11

I thought it was telling that Andrej immediately "reframed" the question because Lex asked the "wrong question". This is a classic evasion technique one learns from experience and/or media training. Lex's comment immediately after was a clever and gentle dig at Andrej's response. It seemed like all the "full cost" negatives Andrej mentioned were related to Tesla's ability to execute, and not what would actually produ…

Devils advocate, if the cost of working to improve cameras to the point where they eliminate that delta is lower than the cost of using the sensors instead, then it is a net benefit

Re: Why Tesla removed radar and ultrasonic sensors [video]

#396

Post by DebtDeflation »

AlotOfReading wrote: post #305
djleni wrote: post #280

Earlier quoted context omitted.

THANK YOU. Reading this thread was getting to me because so many comments say humans drive eyes only. I use far more than just vision driving: - sound, for emergency vehicles, detecting vehicles outside of my field of view if my windows are down or the vehicle is loud, tire sound (especially in snow and rain), engine sound (more feedback in snow or ice about what my tires are doing) - touch (steering feedback, gives…

It's worth noting that most autonomous vehicle solutions have dedicated microphones for emergency vehicles and sensors that can detect slip. I had a little dashboard measuring wheel slip at . It mainly ended up mapping train tracks and potholes.

Do they detect the sound of a motorcycle coming up on them? The sound of a car near you with a flat tire which simultaneously tells you that they will likely make sudden movements to pull over to the shoulder and also to be aware of road hazards that can flatten your tires as well? The sound of brakes locking up tires several cars ahead which tells you to slow down even before the brake lights on the car in front of you illuminate? The sound of detritus hitting the underside of your car which tells you there's likely a larger object ahead that you can't see? There are all sorts of sounds that you're constantly hearing ans subconsciously reacting to.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#397

Post by seanmcdirmid »

underwater wrote: post #345
seanmcdirmid wrote: post #236

Earlier quoted context omitted.

It is a hard question to answer. It’s like asking if more programmers on a project will allow it to be completed faster with higher quality. Ya, theoretically they could, in practice not likely. More sensors are like more programmers, theoretically they can be safer and more effective, but in practice they won’t be. Sensor fusion is as hard a problem as scaling up a software team.

Not more sensors, different sensors. In your metaphor it's like asking if you should have project managers as well as engineers on your project. And Tesla has decided that having only engineers allows them to focusing on having the best engineers. And they avoid the distraction of having to manage different types of employees.

Different sensors are even worse for sensor fusion. Actually, it only applies to different sensors, incorporating different signals with different strengths and weaknesses into a model that is actually better and not worse, is difficult.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#398

Post by seanmcdirmid »

oxfordmale wrote: post #333
seanmcdirmid wrote: post #236

Earlier quoted context omitted.

It is a hard question to answer. It’s like asking if more programmers on a project will allow it to be completed faster with higher quality. Ya, theoretically they could, in practice not likely. More sensors are like more programmers, theoretically they can be safer and more effective, but in practice they won’t be. Sensor fusion is as hard a problem as scaling up a software team.

It is not a hard question to answer at all. LIDAR will make a self driving car safer, period. There is a lot of research to back this up.

LIDAR can be safer than an optical system, I can believe that. LIDAR and an optical system being safer than either alone without a lot of extra complexity: maybe not.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#400

Post by Kerbonut »

funstuff007 wrote: post #380
jholman wrote: post #328

Earlier quoted context omitted.

Uh, that's not at all a good paraphrase. Q: "Does [removing some sensors] make the perception problem harder, or easier?" (note, this is literally what Lex asked, your restatement is misleading) A: [paraphrasing] "Well more sensor diversity makes it harder to focus on the thing that I believe really moves the needle, so by narrowing the space of consideration, I think we'll get better results" Karpathy might not be t…

> because it's often true that you can deliver better by focusing on a smaller number of things. This is true / dogma in linear / non-linear regression world, but of no real import in deep learning or Bayesian methods.

I think they’re talking about number of different systems doing the same thing. Have one system doing it that is sufficiently abstracted away from a common set of hardware vs various systems competing for various aspects of control.
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