Driving dataset for car autopilot AI training

by EvgeniyZh • 10 years ago

100 44 10 years ago

metafunctor2• 10 years ago

This is very cool. I believe scientific papers, especially in the AI space, should habitually share all data that was used so others can repeat and build on the results.

That said, a few hours of highway driving is of course woefully inadequate for learning anything but steering in normal conditions on that particular highway, if even that. So this is not the "build your Tesla Autopilot" kit, even though the OP decided to use the word “autopilot” in the title.

EvgeniyZh2• 10 years ago

This is very cool. I believe scientific papers, especially in the AI space, should habitually share all data that was used so others can repeat and build on the results.

I believe the problem here is that most AI researches are commercial and not scientific, so no data.

even though the OP decided to use the word “autopilot” in the title.

Yeah it might be a bit misleading. Honestly, I had some problems with formulating title in English

metafunctor2• 10 years ago

I believe the problem here is that most AI researches are commercial and not scientific, so no data.

One would hope that OpenAI [1] would come through with some significant data sets for various areas in the future. There are some significant commercial names backing up the initiative (like Musk), so hopefully they will actually be relatively open and not protecting corporate interest until end of time.

[1] https://openai.com/

dharma14• 10 years ago

Most papers use public data sets. I agree there should be more public data sets, for nearly everything.

Having said that - what's the cost of doing something like this yourself? 7 hours of driving video, plus the positional/steering/etc data? Should be easy for almost anyone with enough inclination to gather hundreds of hours of data like this, if you really wanted to.

jacquesm• 10 years ago

I suspect that a certain company whose name starts with a 'G' has been doing just that while at the same time they were filling out their streetview database.

ocdtrekkie8• 10 years ago

The big question for me is... does comma.ai intend to continue to build a public dataset? Because for companies like Google, their primary "value" is their data, that's what they won't share with everyone else, it's what gives them their edge.

If a company was truly willing to share their large datasets down the road, that'd be a Big Deal.

EvgeniyZh2• 10 years ago

When you think about it, at least in Russia many people have video cameras in their cars, and you probably can buy their data for relatively small money, acquiring many hours of driving video. I'm surprised no company have done it yet.

dharma14• 10 years ago

I guess it could get quite hard to share public data sets like that once you get into hundreds of terabytes of video.

I'd say for autonomous cars it's the ML algorithms, rather than the data that's the threshold. I'd wage it would be relatively inexpensive for even smaller companies or researchers to pay a delivery/taxi/whatever company a small amount for a few thousand hours of dashcam footage

bbayer• 10 years ago

Author George Hotz, also known as geohot, is the author of first working iOS jailbrake. He decided to enter self driving car area[1]. Apparently he founded a new company called comma.ai [2]

[1] http://www.bloomberg.com/features/2015-george-hotz-self-driv...

[2] http://comma.ai/

denzell• 10 years ago

Once I read George Hotz.. I knew i recognized the name.

IshKebab2• 10 years ago

Cool, but this really confirms what I suspected about Hotz's car all along. He's just done the 'easy' bit - output steering angle on easy highways. That was done in the 80s (slower admittedly, but still).

Wake me up when it can drive here (to pick a random example):

https://www.google.co.uk/maps/place/London/@52.1986058,0.143...

nobody_nowhere• 10 years ago

Or in a snowstorm.

ocdtrekkie8• 10 years ago

I think Ford is the first company to really be trying to test in snow at all, but that's mostly focused on mitigating the problem of snow on the ground. The sort of snowstorms I've driven in, I don't expect a self-driving car to be able to do in the next sixty or seventy years at least.

ocdtrekkie8• 10 years ago

Pretty much all most self-driving efforts has done is "the easy bit". Google's record is primarily focused on bragging about miles driven. And glossing over the fact the hundreds (or thousands?) of times their test drivers have to take over, presumably in difficult areas like intersections. If you see someone bragging about their "miles driven" as a key statistic, you should be wary of their actual accomplishment. Because racking up miles down a straight stretch of road is easy.

There's a massive amount of hype in the area, and a terrifyingly small amount of actual substance.

Retric4• 10 years ago

Google is driving in urban traffic which is never easy. Tesla is being driven 'by customers' an thus out of the companies control.

Look at any of the accident tapes and these are generally situations where people would likely also cause an accident. Just look at the number of people rear ended for daring to stop at a stop light.

Fricken• 10 years ago

Comma.ai has stated their goals very clearly: they want to sell a retrofit kit you install yourself for under $1000 that allows level 3 autonomy under optimal circumstances, that being highway/freeway driving in good weather conditions.

mbesto• 10 years ago

So uhh what happens when the weather conditions change? Will the system automatically turn off it's autonomous function and let you take over?

dharma14• 10 years ago

Right. I wonder which year this will launch, and how long it takes until the first death

revelation• 10 years ago

And why would people buy that? That pretty much comes standard nowadays on a somewhat more high-end Mercedes, giving you a fully integrated system with the added bonus that your insurance won't refuse to cover you because you installed an unproven startups Python deep learning steering wheel.

I'm being facetious but this is how this will work out in the end for the first early-adopter to get into a crash.

Animats3• 10 years ago

That's not a hard case. It's just a narrow, straight road lined with obstacles. If you have sensors that can get a height field, that's no problem. Our DARPA Grand Challenge vehicle could have done that in 2005, using a LIDAR. Google wouldn't have any problem with that. Tesla would have a problem; they're dependent on lane lines.

ghaff2• 10 years ago

The main difficulty with a side street like that is there isn't actually enough room for 4 vehicles across--2 parked and 2 going in opposite directions. Humans can deal with this pretty easily because it's usually fairly obvious who can most easily yield or even back up a little bit. It's not an especially hard problem and 2 vehicles that could formally communicate would make it easier yet. However, if the behavior depends on essentially social signals, that's somewhat harder but far from impossible to model. (You probably program the computer to politely yield if at all possible.)

However, as you say, this is yet another case where vehicles aren't expected to unthinkingly follow lane lines--if they even exist.

taco_emoji• 10 years ago

The point is that this is a two-way street with (effectively) only one lane, so regardless of how good your sensors are, your AI needs to predict and react to the actions of oncoming cars in order to successfully navigate this road.

IshKebab2• 10 years ago

As taco_emoji said, the difficulty is not avoiding the obstacles. What happens if a car is coming the other way. Do you reverse? Do you let them reverse? Did they flash you? Are they waiting in a 2-lane section? Should you wait? What if it's a bike instead - can you both fit?

Way more difficult than "don't hit the sides".

edward• 10 years ago

Great example, this road is half a mile from my house. I've been wondering how self driving cars will deal with a street like this.

Animats3• 10 years ago

This creates a model for driving that totally ignores things that can go wrong. It will work great in the normal case, and totally screw up if anything unusual happens. There's no model of "obstacle" or "oncoming vehicle". That's unsafe.

This is a field where bug reports are written in blood.

Driving dataset for car autopilot AI training

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