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Driverless Hype Collides with Merciless Reality

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Re: Driverless Hype Collides with Merciless Reality

#191
post #178

Earlier quoted context omitted.

How would we get accurate information on the number of lives Tesla's "autopilot" has saved?

Humans die on average every 80 million miles driven ( not sure the metric for highway miles only ), but prove that Tesla can beat that metric and you can assume lives are being saved.

not so fast. youneed to compare tesla death per mile withother high end sedan death per mile. comparing a population of all cars include a lot of less secure cars, like city cars, old cars and cars that haven't enjoyed the same level of maintenance a driver with high income can afford.

iow tesla needs to beat the average 2014+ 3 series death per mile.

Re: Driverless Hype Collides with Merciless Reality

#192
post #94

Earlier quoted context omitted.

I'm sorry I can't back up my claims but you will be proved wrong with time. I would bet in less than 10 years you'll have camera only fully autonomous systems.

From Sterling Anderson, former director of Autopilot who oversaw the implementation of HW2: >Perception is a game of statistics.Crudely speaking, if we have three independent modalities with epsilon miss-detection-rates and we combine them we can achieve an epsilon³ rate in perception. In practice, relatively orthogonal failure modes won’t achieve that level of benefit, however, an error every million miles can get b…

He is basically just saying that the errors need to be independent, so you can get that with different capture mechanisms. I think that is wrong. For example, small, fast and poorly reflective will have similar detection performance for lidar and cameras. I think that the real problem is getting consistent statistical estimators and fusing them at a useful update rate. Has anyone seen the lidar from the uber crash? It would be interesting to see if a person could "tell" that the poor pedestrian wasn't an artifact quickly from lidar alone.

Re: Driverless Hype Collides with Merciless Reality

#193
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…

Geometry inferred from range sensors can certainly provide an additional useful source of information, but it's far from clear that the right approach to controlling a self-driving vehicle is mostly to solve a geometry problem. For example, even if a range sensor can provide a perfect estimate of the location and geometry of pedestrian, how do you predict whether the pedestrian will dart out into the road or stop because they see a car coming. Human drivers have learned from years of (mostly) visual experience observing human behaviors to make reliable predictions about such things. Perhaps machines can too.

Since evolution didn't provide us with our personal lidars, human drivers are an existence proof that it is possible to learn reliable driving performance from vision alone. Which isn't to say that machine learning based on vision alone is already close to human-level or competency or that human-level competency is sufficient for a automated driving system or that sophisticated sensors don't make the problem a bit easier. But I don't know how you can be so confident that vision alone (or primarily) won't be route that eventually succeeds.

Re: Driverless Hype Collides with Merciless Reality

#194
post #182

Earlier quoted context omitted.

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 100% attention thing I why I have tremendous faith that computers will be out-driving humans in short order. Even really good human drivers have a limited perspective and focus. And even the best human drivers are subject to emotional state.

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 self-driving car needs.

You gotta figure out if there's a still-object on the road. And whether or not its a shadow (shadows don't move after-all but its safe to drive over). Like, neural networks can't do that stuff 100% reliably yet. And it may never happen.

Or some researcher next year might come out and discover a method to parse background / foreground / shadows out of pictures. But then there are a whole host of OTHER issues involved.

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I think self-driving technology has potential. But you need more than just neural networks hooked up to cameras. I really like Waymo's direction with advanced super-human sensors. Avoid the shadow / background / foreground problem entirely and just have LIDAR give you the precise coordinates of all objects within 100-feet of the car.

IMO, if self-driving technology ever happens, it will be because of advances in advanced LIDAR or other kinds of sensors. Stuff that can avoid the research-problems that the "Deep Learning" community hasn't been able to solve for the last 50 years.

Re: Driverless Hype Collides with Merciless Reality

#195
post #170
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…

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…

> It was designed for binocular vision

Does binocular vision even matter at such distances (i.e. beyond a few meters)? I thought it was only effective for relatively close objects.

Re: Driverless Hype Collides with Merciless Reality

#196
post #112
post #94

Earlier quoted context omitted.

I'm sorry I can't back up my claims but you will be proved wrong with time. I would bet in less than 10 years you'll have camera only fully autonomous systems.

Have you ever heard about that thing called fog?

Cars could communicate together though

Re: Driverless Hype Collides with Merciless Reality

#197
post #178

Earlier quoted context omitted.

Humans die on average every 80 million miles driven ( not sure the metric for highway miles only ), but prove that Tesla can beat that metric and you can assume lives are being saved.

not so fast. youneed to compare tesla death per mile withother high end sedan death per mile. comparing a population of all cars include a lot of less secure cars, like city cars, old cars and cars that haven't enjoyed the same level of maintenance a driver with high income can afford. iow tesla needs to beat the average 2014+ 3 series death per mile.

You also need to account for the regions where Teslas are most popular, the demographic of people who are purchasing Teslas, cars with similar safety features, and many other factors. Comparing the very tiny slice of the market which drives Teslas against every other car+driver on the road is almost meaningless.

Re: Driverless Hype Collides with Merciless Reality

#198
post #150
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…

> You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning. What you wrote makes a lot of sense to me. However, I would also hope that in a matured self-driving environment, traffic lights would be mapped ahead of time. It's always possible that a traffic light shows up in an unexpected place, but in my mental image of the future, this raises a flag for system management to modify…

> There is a chance that a powered non-permanent traffic light is found somewhere, a dude walking along the side of the street with a stoplight on his back

Temporary traffic lights are extremely common, at least here in Australia. They are used in the case of roadworks or other short-term disruptions that requires traffic flowing in both directions to share a single lane, in conditions not suited to manual traffic control (i.e. overnight, weekends, long-term works on rural roads).

http://www.datasigns.com.au/Products/Portable-Traffic-Lights

Re: Driverless Hype Collides with Merciless Reality

#199

Earlier quoted context omitted.

rail and bus infrastructure is never going to be feasible in the small town in Texas where I grew up, 1.5 hrs from Ft. Worth. Not to mention all the even smaller towns in that county and the counties around it. How is one supposed to move 3 horses across the state using rail and buses? What about my parents driving to surrounding lakes to kayak? Just cary that on a train that for some reason actually goes to these la…

No offense, but this conversation is not for you or your family. The car is the second best thing that ever happened to rural life, after the tractor, and nothing is going to change that. This conversation is about the 62% of Americans that live and work in 3.5% of the land area. (Source: https://www.census.gov/newsroom/press-releases/2015/cb15-33.... ) There’s no reason for rural America to act like these ideas are…

Oh, that's not offensive.

FWIW those 62% live in "incorporated paces" or cites, which would include my town (as long as I'm understanding that correctly.) Down under "new incorporated places" it mentions Sandy Point, TX, population 200. It's crazy that even including little towns like that you're still only talking about 3.5% of the land.

Re: Driverless Hype Collides with Merciless Reality

#200
post #150
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…

> You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning. What you wrote makes a lot of sense to me. However, I would also hope that in a matured self-driving environment, traffic lights would be mapped ahead of time. It's always possible that a traffic light shows up in an unexpected place, but in my mental image of the future, this raises a flag for system management to modify…

It's relatively common for road maintenance crews in rural areas to install temporary signal lights during major projects. For example when they close one lane on part of a two lane road so traffic can only move in one direction at a time while the drivers going the other direction have to wait a few minutes.
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