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Autonomous DeLorean drives sideways to move forward

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Re: Autonomous DeLorean drives sideways to move forward

#31

Post by sudhirj »

saagarjha wrote: post #7

I was half expecting a Toyota Sprinter Trueno and Eurobeat. Pop references aside, though, what is this useful for? I thought cars were designed to not skid normally due to ABS?

ABS is a very human-centric system the tries to keep the car controllable under low traction, often by sacrificing something aspect of movement. The neural nets here throw all that out of the window, and control the car with direct physics, without being once or twice removed from reality.

The video also has some very interesting points about how the AI should be able to control the acceleration and braking on each wheel individually - so we really don't need to limit AI driving with human safety or control systems.

Re: Autonomous DeLorean drives sideways to move forward

#32

Post by ohadron »

Somewhat reminds the progress airplanes did in the 1970s with fly-by-wire technology. Specifically they way it was utilised in the F-16.

Moving from directly piloted controlled surfaces (rudder, elevator, flaps, ailerons etc) to using a computer to convert the pilot command input to servo actuators. Flight surfaces had much more authority, much better performance could be achieved, but the flight computer was in charge of safety and keeping the aircraft within limits.

https://en.wikipedia.org/wiki/Fly-by-wire

Re: Autonomous DeLorean drives sideways to move forward

#33

Post by godelski »

Animats wrote: post #6

They did most of that back in 2015.[1] This is version 2. It's interesting what's happening as the control theory people get into machine learning. The controls people don't typically run a neural net as a controller. They use the trained net as a tool for building a controller with known continuity properties. The trouble with pure neural net controllers is that they sometimes do something totally bogus for some dat…

Anyone have more technical information on this? This sounds really cool.

Re: Autonomous DeLorean drives sideways to move forward

#35

Post by sillysaurusx »

AndrewKemendo wrote: post #12
Animats wrote: post #6

They did most of that back in 2015.[1] This is version 2. It's interesting what's happening as the control theory people get into machine learning. The controls people don't typically run a neural net as a controller. They use the trained net as a tool for building a controller with known continuity properties. The trouble with pure neural net controllers is that they sometimes do something totally bogus for some dat…

>They use the trained net as a tool for building a controller with known continuity properties. This sentence and comment is a revelation to me so thanks! I was very into control theory from 2001-2006 before jumping into Bayes nets and eventually ML. Having not really returned to CT since, it's always been a question in my mind how to use ML for SCADA & PLCs without running into the problems that you describe. As wit…

I would highly recommend https://www.youtube.com/watch?v=PYylPRX6z4Q as a way of framing the problem.

It seems like our options for ML are currently: self-play, dataset fitting, or human feedback. It's possible to solve any problem that can fit into one of those molds.

(Unfortunately the opposite is true: if a problem doesn't fit into those categories, it seems very hard to solve with any form of ML.)

But, now that I think about it a bit more, the sentence "use a trained net as a tool for building a controller with known continuity properties" seems neither obvious nor straightforward to do. I'm decently well-versed in AI techniques at this point, and I can't really think how I'd sit down and write a program that would generate such a system. Anyone have any leads?

Basically, the goal is to make a neural net that helps you design a system that can be predictable. One way would be to write a loss function that penalizes unpredictability, and then let it run until it converges on a predictable control system. But that's a bit like saying "Just draw an owl." Not so easy to think of the actual code to do that.

Re: Autonomous DeLorean drives sideways to move forward

#37

Post by mmerlin »

jamestimmins wrote: post #9

So is the general idea that by removing the automated controls, which normally limit drift so human drivers don't lose control, they're able to gather data at the extremes of car handling? I'm curious how this would be applied in the real world. It almost seemed to suggest that a self-driving car would operate with those stability controls turned off, allowing it operate evasive maneuvers that would be impossible in…

I'd like to see this car vs humans in the Hyperdrive series on Netflix

Re: Autonomous DeLorean drives sideways to move forward

#38

Post by dmckeon »

joshu wrote: post #30
campfireveteran wrote: post #27

Earlier quoted context omitted.

Yeap. That's where I sent my roommate from college to learn performance driving; a Korean dude with a CS degree from an UC turned California highway patrol (CHP) officer. (How many cops has anyone ever run into understood Big-O notation?) Disclaimer: I learned a thing or a thing and half sliding around the back roads of the Sacramento levee system with water hazards on both sides. }:]

i did a track day up there years ago who was chp and was trying to explain you had to take trigonometry to me for taking the radar speed of a vehicle at an angle...

Vehicle speed within traffic lane, or relative speed along a vector to/through the radar device - which vector might be at a significant angle to the traffic lane?

Re: Autonomous DeLorean drives sideways to move forward

#39

Post by charliepark »

Animats wrote: post #6

They did most of that back in 2015.[1] This is version 2. It's interesting what's happening as the control theory people get into machine learning. The controls people don't typically run a neural net as a controller. They use the trained net as a tool for building a controller with known continuity properties. The trouble with pure neural net controllers is that they sometimes do something totally bogus for some dat…

> "The trouble with pure neural net controllers is that they sometimes do something totally bogus for some data point within the normal input space."

A friend's theory on Google Maps is that it sometimes intentionally sends you down a non-optimal path in order to gather data on alternate routes. This friend isn't in the ML space, so this is just their anecdotal observation. Are they right, then?

Re: Autonomous DeLorean drives sideways to move forward

#40

Post by dharmab »

jamestimmins wrote: post #9

So is the general idea that by removing the automated controls, which normally limit drift so human drivers don't lose control, they're able to gather data at the extremes of car handling? I'm curious how this would be applied in the real world. It almost seemed to suggest that a self-driving car would operate with those stability controls turned off, allowing it operate evasive maneuvers that would be impossible in…

Drifting is objectively less effective and safe than normal manuevering and braking.

Drifting as a sport exists to look cool and stylish. It's like figure skating with cars.

(There is one exception- off road racing on loose surfaces requires drifting. But driving that way off road is only useful for speed at the expense of safety and reliability.)

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