Comment by paxys
3 days ago
Driving through an obviously flooded street thinking "I'll easily make it" and getting stuck in the middle? Yeah, these cars have achieved human level intelligence.
3 days ago
Driving through an obviously flooded street thinking "I'll easily make it" and getting stuck in the middle? Yeah, these cars have achieved human level intelligence.
That being said... it's actually somewhat uncommon for humans to drive into flooded streets. To the degree that people think it's notable enough to take videos and post them to social media. I don't have the data, but would be interested to see how many times per passenger mile travelled human-directed and remotely-operated vehicles like Weymos drove into flooded streets.
I can appreciate the cameras and lidar on the Weymos don't give their remote operators a lot of good data about the depth of water on the road-way. As you point out, humans in cars often don't get this right. I think the humans that don't drive into deep water are the ones who a) give any amount of water on the roadway a big NOPE and b) people familiar with the local environment and use multiple visual clues to judge the true depth of the flooding.
It shows up on social media when it’s a rare event for that area. It’s uncommon but “happens all the time” here in California in the deserts every heavy rain either because locals forget how deep the flood control washes are, or because tourists just drive into them thinking its a straight road, despite all the signs and warnings posted around them.
As far as I can tell from these articles, driving into a flood has happened twice to Waymos, once in Texas and once in Atlanta? It does seem like it's pretty uncommon.
Ask the car, in the sense you can, why it drove into the water.
Then ask the human.
I'm not sure you'd walk away the idea that they have equivalent intelligence. The human at least knew the water was there and took a risk, the car, presumably, had no idea what was in front of it and drove into it anyways.
Just get a jeep snorkle
What happens when you you start floating?
I guess water propulsion... and a rudder?
You need to get an armored jeep then
A decent welder should be able to turn out a trailer hitch <=> outboard motor bracket in under 15 minutes. It's not like you'll need much more than a modest fishing outboard to get through flooded spots.
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jeep snorkels are for air intakes for engines. electric cars don't have air intakes. they have air cooling for batteries... I suppose you could snorkel those.
Depends on the EV. Some of them have liquid cooling for their battery pack.
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[flagged]
> Please don't post comments saying that HN is turning into Reddit. It's a semi-noob illusion, as old as the hills.
https://news.ycombinator.com/newsguidelines.html
Yeah was a joke as I think most cars if you drive through that your car is f'd
Ironically, a properly sealed EV system would better deal with a flood. Combustion engines have issues due mostly to the air intake and exhaust.
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Their account is about as old as yours.
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People are allowed to joke. We don't always need 'substantive comments'
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Let’s redirect the problem: it’s not the car, it’s the flooding! We should address that first
This is why I personally feel like Tesla's approach is more likely to "win". The fundamental blocker to self-driving cars is not sensing / sensor fusion, it is intelligence. And the Tesla approach seems much more likely to achieve functional intelligence than Waymo's.
While I agree with basically all of this, and find the FSD on my Tesla to be quite useful, a question pops into my mind.
Why can't Waymo ALSO develop the same smarts and just also solve the sensor fusion issue such that they can use the right set of sensors in the right environmental conditions, and then leapfrog Tesla's capabilities?
Because they don't have a fleet of millions of people labeling the data for them and paying for the privilege of doing so. Waymo has about 3700 vehicles. Tesla has millions. Waymo only operates in known environments and collects a very limited range of data. Tesla collects data everywhere that people drive their cars.
I thought about this and I think it boils to how the model is trained.
Tesla trains it models from actual drivers purely based on (input) Vision and (output) actuators - Brake, Steering, Accelerators.
Human output is based on what they and the camera sees. So, it's a 1:1 match.
If Waymo were to do that, it'll muddle the training set. The Lidar input may override camera input.
I always struggled when Musk mentioned Lidar will make it ambiguous. It didn't make any sense to me why having a secondary failback sensor messes things. But, if you put it in the training data context, it absolutely makes sense.
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> such that they can use the right set of sensors in the right environmental conditions
Because this part is really hard, and that's why Tesla abandoned the fusion approach. You cannot possibly foresee all the conditions in which LIDAR or any active sensor will malfunction/return wrong data/return data that's only slightly off for that ONE specific time. And even if it doesn't, you need to trust it to not return noise. And when it does return noise, how do you classify it as noise?
Cameras are passive sensors - they get whatever light comes in and turn it into an image. Camera is capturing shapes that make sense to the neural nets: it's working. See all black/white/red/cannot see any shapes? Camera is not working, exclude it from the currently used set of sensors or weigh it less when applying decisions, because it's returning no signal (and yes, neural nets have their own set of problems).
EDIT: cameras also provide more continuous context: if 1 pixel is off, is clearly bright red in a mostly-green scene where no poles can be identified, the neural net will average it out and discard it as noise. If 1 pixel says "object" in LIDAR, do you trust it to be correct? Perhaps the ray just hit a bird or a fly, but you only see a point, it's a lossy summary of the information you need.
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They could in theory. If they put at least as much emphasis on the AI side as Tesla does. Or if someone else cracked vehicle AI wide open and left it open for them to copy, and then they did exactly that, and found a way to bolt on their extra sensors in a useful fashion while at it.
As is, Waymo's playing it smarter than Cruise did, but they're not all in on AI yet. So I don't expect them to "leapfrog Tesla" in that dimension - and it's the key dimension to self-driving.
The main reason Tesla's don't have LIDAR is hardware cost and maintenance cost, not improved safety.
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I got downvoted for saying this last time the topic came up but constraints focus a project. It’s best to start work with as few variables as possible, and only add new ones when absolutely necessary.
I'm working on a similar problem in computer vision and we're quickly approaching the point where our pure vision work is better than our Lidar supported track because we've had to deal with the constraints instead of having a crutch to lean on.
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You can have intelligence with lidar.
You can have even more intelligence with both.
You can have your cake and eat it too?
Sensor fusion isn't free. Lidar requires more power consumption and more onboard compute. Cycles that could be spent on "intelligence" are instead being spent on sensing.
I like both approaches. The fact that both exist is a clear win for the rest of us as consumers.
Tesla's approach seems like a bet that A) AI will reach human-level driving intelligence before lidar becomes cost-efficient, in which case their current sensors will be sufficient to achieve at least human-level performance; and B) ~human-level performance will be sufficient to achieve large-scale consumer and regulatory acceptance. Waymo seems to be taking the other side of that bet.
If Tesla is right, their solution should scale faster, and they can worry about adding superhuman sensory capabilities later. If Waymo is right, all the Cybercabs that Tesla is pumping out right now are destined for the scrapyard, or at best will spin their wheels in beta testing for years while Waymo speeds ahead.
Tesla is putting its money on the bull case for self-driving as a whole. If Tesla wins that bet, it means we all get access to a useful version of the tech years earlier. If Waymo wins, that's great too, but it means that for better or worse lidar will be a bottleneck to scaling the tech.
The whole thing is basically a rehash of Intel vs TSMC on EUV in the 2010s.
Naaah, Tesla has no edge in intelligence either. It's just a PR piece to sell to investors.
They never advertised that they did. Its not even real true AI. They just struggle with new scenarios.
People drive into floods too. They just don't get sensational articles written about it, just posted on reddit.
Taxi drivers with passengers don’t tend to though. At least not at the same rate.
Whoosh...