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Driverless Hype Collides with Merciless Reality

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Re: Driverless Hype Collides with Merciless Reality

#211

Post by beat »

nutjob2 wrote: post #142
ModernMech wrote: post #132

Earlier quoted context omitted.

As an existence proof, people drive through fog every day. We prove that it's possible to take binocular visual data and convert that into a series of control signals that will propel a car through fog. Sure sometimes accidents happen, but every day thousands upon thousands of people safely navigate fog in e.g. San Francisco or London. I see no reason machines shouldn't be able to perform at least as well one day.

> I see no reason machines shouldn't be able to perform at least as well one day. Assuming that day is infinitely far away, then you're right.

Why? What's magical about human beings that a sufficiently advanced sensor and sufficiently advanced AI can't do the same responsive task?

If there's magic in the human mind at all, it's the creative side of the mind. Driving isn't a creative act.

Re: Driverless Hype Collides with Merciless Reality

#212

Post by Fricken »

linuxftw wrote: post #209
Fricken wrote: post #202

Earlier quoted context omitted.

The infrastructure driverless vehicles rely on is their own internal maps, which have lanes and signage marked out. Being able to visually detect these things is important, but it is a measure for added redundancy. Great strides have been made in using machine learning to filter out obscurants such as snow. Perception for autonomous vehicles is effectively a solved problem. The biggest technical challenges are relate…

> Great strides have been made in using machine learning to filter out obscurants such as snow. Perception for autonomous vehicles is effectively a solved problem. Great strides is not 'perfected' and I don't think perception for autonomous vehicles is a solved problem whatsoever. What is a driverless car to do if it slides out of position on the road and is now facing the wrong direction? Does it have the ability to…

The two key aspects of an autonomous OS are perception and planning. Being able to "see" well enough during a flurry is a perception problem. Knowing whether to maneuver out of it or call for help after spinning out is a planning problem. There are many planning problems left to address and master before autonomous vehicles are ready for widespread adoption. Some planning problems are unique to specific intersections, and dedicated software has to be written just for that intersection, like the intersection of Market and Castro, in SF, for instance.

Re: Driverless Hype Collides with Merciless Reality

#213

Post by dragontamer »

beat wrote: post #206
dragontamer wrote: post #194

Earlier quoted context omitted.

Yeah, humans suck at attention. But until we can program computers to tell me what is a foreground moving object, what is a shadow, and what is the background... you literally can't solve the "Should the car apply the brakes right now" problem. https://arxiv.org/pdf/1801.02225.pdf Just go through this recent paper I found on DDG.gg and see the amount of effort it takes to parse foreground / background data that a sel…

That's why I think the future lies with a mix of (possibly layered) sensing and decision-making technologies. LIDAR + cameras + downloaded maps + machine learning + whatever. The "until we can program computers to..." is a when question, not an if question. There's nothing about driving, in any situation, that doesn't fall in the face of "assuming infinite computing power and infinitely good sensors". Driving isn't a…

I think that's reasonable, although our time estimates for when this problem solved may disagree.

My main issue is that a large number of people seem to think that cameras + machine learning are enough to solve this problem. And while I'm not an expert at machine learning, what I know about it makes me a pessimist. There's just too many unsolved problems in the machine-learning community to apply machine learning to the car-driving problem.

Machine learning probably can solve weird cases people don't expect. IIRC, CNNs are better at recognizing blurred or garbled text than humans these days. So CNNs can read speed limit signs, road signs, and other texts and and at least process that.

Even figuring out if its a speed limit sign, an address, or a route-number probably can be solved by CNNs. But higher level reasoning (is that spraypaint messing up the signpost?? Which was common in some of the areas I drove through) seems like an unsolved problem.

----------

Anyway, Machine Learning + Cameras are IMO, at best... a partial solution to some of the problems. Anyone who thinks that cameras + radar + machine learning is sufficient is probably just a TSLA long who wants to believe in the success of their stock. Otherwise, I think most people are reasonable and recognize the importance of experimenting with a ton of different methodologies to solve this problem.

Re: Driverless Hype Collides with Merciless Reality

#214

Post by thanatropism »

01100011 wrote: post #201
pkulak wrote: post #170

Earlier quoted context omitted.

No one thinks that you just hook up ML to a camera and you're done. Literally everyone working on this only uses ML for identification. When that Model X crashed into a highway divider, it was because the lines on the road were very faint and there was a fork in the line that actually wasn't the _real_ lane line. The car followed that by mistake, but only because of the misidentification of the lane line. How are mor…

Well, my optical sensors(i.e. eyes) provide me with enough information to discriminate a cat from a bag, so I suppose with enough processing we should be able to do the same with a control system. Cars have an added advantage that their vision systems could work in lower light and non-optical wavelengths. I don't see any fundamental issues with getting self-driving cars working. It may not happen in 5 years, but it w…

Yes, but your machine learning algos are much much better.

Re: Driverless Hype Collides with Merciless Reality

#215

Post by saltcured »

JBReefer wrote: post #160
anticensor wrote: post #131

Earlier quoted context omitted.

Self-driving car: ZF Electric car: ZF TaaS: ZF Self-driving advertising services: ZF All will be available, all from the same company. EDIT: Waymo laughed at "route-based advertising" when I mentioned, but ZF supports this idea. Route-based advertising or route advertising is an advertising model where your vehicle diverts to make you see a particular place and/or get you to visit a particular shop. For example, it m…

That is extremely dystopian

It sounds like the touts who circle airport arrivals like vultures, looking for tourists to take for a ride...

Re: Driverless Hype Collides with Merciless Reality

#216

Post by newnewpdro »

erikpukinskis wrote: post #95
Animats wrote: post #71

Driverless cars are coming along just fine. Waymo is making steady progress. The sensors are getting better. The problem comes from all those "fake it til you make it" startups, Uber and Tesla being the worst. Both have killed people. This is mostly about sensors and geometry. Machine learning has a role, but only in target identification. That's how Waymo does it. The fake it til you make it crowd had the fantasy th…

Hasn’t Tesla autopilot saved more lives than it took? So it’s more net beneficial (so far) than cautious Waymo?

You're drinking some strong kool-aid.

Re: Driverless Hype Collides with Merciless Reality

#217

Post by linuxftw »

Fricken wrote: post #212
linuxftw wrote: post #209

Earlier quoted context omitted.

> Great strides have been made in using machine learning to filter out obscurants such as snow. Perception for autonomous vehicles is effectively a solved problem. Great strides is not 'perfected' and I don't think perception for autonomous vehicles is a solved problem whatsoever. What is a driverless car to do if it slides out of position on the road and is now facing the wrong direction? Does it have the ability to…

The two key aspects of an autonomous OS are perception and planning. Being able to "see" well enough during a flurry is a perception problem. Knowing whether to maneuver out of it or call for help after spinning out is a planning problem. There are many planning problems left to address and master before autonomous vehicles are ready for widespread adoption. Some planning problems are unique to specific intersections…

Can they perceive where on the road they should be located when the road is totally covered in snow and you can't see the pavement, let alone the line markets, possibly only tire tracks, if that?

Re: Driverless Hype Collides with Merciless Reality

#218

Post by eddieplan9 »

01100011 wrote: post #201
pkulak wrote: post #170

Earlier quoted context omitted.

No one thinks that you just hook up ML to a camera and you're done. Literally everyone working on this only uses ML for identification. When that Model X crashed into a highway divider, it was because the lines on the road were very faint and there was a fork in the line that actually wasn't the _real_ lane line. The car followed that by mistake, but only because of the misidentification of the lane line. How are mor…

Well, my optical sensors(i.e. eyes) provide me with enough information to discriminate a cat from a bag, so I suppose with enough processing we should be able to do the same with a control system. Cars have an added advantage that their vision systems could work in lower light and non-optical wavelengths. I don't see any fundamental issues with getting self-driving cars working. It may not happen in 5 years, but it w…

An intelligence animal being able to do something != "with enough processing we should be able to do the same with a control system".

Re: Driverless Hype Collides with Merciless Reality

#219

Post by andrewaylett »

beat wrote: post #179
photos_victim wrote: post #159

Earlier quoted context omitted.

How did you conclude this? There are other similarly-priced but more-numerous models of car where literally nobody has ever died after crashing one. Controlling for price (as a proxy for the wealth of the occupants) Tesla has a poor safety record.

Cite?

https://www.telegraph.co.uk/news/2018/04/15/britains-safest-... for example: "no drivers or passengers killed inside it in the 16 years it has been on sale", with 50k sold in the UK.

Re: Driverless Hype Collides with Merciless Reality

#220

Post by thanatropism »

dragontamer wrote: post #130
fabiospampinato wrote: post #117

Earlier quoted context omitted.

> The fake it til you make it crowd had the fantasy that you just hook up some cameras to a machine learning system, train it, and you have self driving. There are about 7 billion instances of those learning systems though. Will this be replicated with machines in the next 10 years? I have no clue. Is this doable at all? Sure.

There's absolutely no equivalence between a CNN created today with deep learning, compared to the Neural Network in a human brain. The problem with the human brain is one of inattention. CNNs / Artificial Neural Networks can remain at attention 100% of the time due to their artificial / machine nature. But CNNs, despite being at 100% attention the entire time, still have issues determining if that splotch on the scre…

The "neural network" terminology is really cringeworthy all things considered. ("Deep learning" is much better.)
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