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Tempe Police Release Video of Uber Accident

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Re: Tempe Police Release Video of Uber Accident

#901

In my mind this accident is on Uber no matter how you interpret the video. Scenario 1: Lets say the pedestrian was visible to the naked eye and sensors. The model and safety operator still didn't "see" her and act in time. Who to blame? Uber. Scenario 2: The lighting and environment was in a condition where neither the model nor the safety operator could see the road more than 10 feet in front of the car, yet neither…

I think we should be able to transfer the guidelines that apply to train drivers. There they spend hours and hours on end doing practically nothing and certainly not steering.

However I'm guessing that the Uber test drivers don't get paid anywhere near as much as a train driver or given the same kind of training.

Re: Tempe Police Release Video of Uber Accident

#903
This reminds me of a Google story from two years ago.

"A Cyclist's Track Stand Befuddled One of Google's Self-Driving Cars"

https://gizmodo.com/a-cyclists-track-stand-totally-befuddled...

Perfect example of a corner case. I do NOT believe you can kind of be driving and so having a safety driver means little. The software has to be able to handle this type of situation or should not be on the road.

I get it was crazy for this lady to be in the middle of the road in complete darkness. But this is the EXACT situation you would have thought a SDC would perform far better then a human.

What is really needed is some way to replay this in data against others algorithms and see what they would do.

Love to see what Google would have done? I also worry in trying to keep up with Google these companies are doing very unsafe things. Uber would be far better off just using Google technology.

Re: Tempe Police Release Video of Uber Accident

#905

The first question that comes to my mind watching this, is, why didn't the _pedestrian_ see the _car_? It looks as though she didn't even look up until the car was only a few feet away from here. I'm not just trying to "blame the victim". The car "should" have responded sooner. But see-and-avoid works both ways. If you're choosing to cross a road in the dark, you, too, have a responsibility to understand the drivers'…

THere are several lanes free with plenty of room for the car to pass without issue. I think the pedestrian assumed this was just an inconsiderate driver not slowing down and driving around me... as there is no way on earth that a human would ever have hit her! the video is totally unrepresentative, and if it was representative then the car should have been doing half the speed.

Re: Tempe Police Release Video of Uber Accident

#906
post #849
post #818

Someone on Reddit posted a comparison of the same spot at night but with a good camera: https://m.imgur.com/a/PM7uu from a video at https://www.youtube.com/watch?v=1XOVxSCG8u0 That paints the whole accident in a very different light from the video from Twitter. Would any human not notice someone crossing in the good camera screenshot?

Yep, also this HDR image of the scene at night: https://imgur.com/gallery/XQrAB Really hope the cops didn't just look at the low-dynamic range dashcam video and decide it's case-closed here. I would not want one of these Uber cars on the streets with me.

NTSB is investigating the crash, so surely they'll conduct adequate forensics work.

Re: Tempe Police Release Video of Uber Accident

#907
post #584

This was the original story: "After the Uber collision, the car continued traveling at 38 miles per hour, according to the Tempe police chief" https://www.bloomberg.com/news/articles/2018-03-21/for-self-... In other words, the car _never_ detected the pedistrian and never slowed down on its own. This has nothing to do with _when_ it saw her. It clearly didn't, yet both camera and LIDAR should have been able to.

This doesn't even make sense, we can see in the video that the "driver" does look up and react. Why didn't they hit the brakes?

Re: Tempe Police Release Video of Uber Accident

#908

The description given before the video was released painted a picture in my mind that the woman was on the median and "suddenly" entered the roadway in front of the vehicle. I pictured someone darting across the road directly in front of the car, with no way to stop in time. This video shows a completely different scenario. The woman started on the median, but the vehicle was in the #2 lane. She wasn't visible to the…

Indeed; I'm wondering why the police were so fast to say that the woman suddenly entered to road, when the video shows this clearly isn't the case.

I bet the police chief who gave the quotation saw that video once and was startled at how suddenly the person appeared in that video and didn't check and see things like there was another lane or anything about the surroundings.

Re: Tempe Police Release Video of Uber Accident

#909

So now we all know- Elaine Herzberg did not run out in front of the car, as the police said, she was walking at a normal pace; she was not in the shadows- the camera footage is typically darker than human vision; and the reason why the first thing the driver knew of the crash was the sound of it is because she didn't have her eyes on the road. And all the cars sensors, its superior perception of its environment and i…

You're missing the (admittedly comfy) narrative that the other tech companies are being diligent and careful while Uber are a bunch of cowboys rushing alpha code out into public, who only change stuff when they get caught. The autocar fan's worst nightmare.

I noticed that trend in comments, yes. Unfortunatly, the real issue with what Uber or Waymo (or anyone else) are doing it's with the limitations inherent in the technology itself, specifically, machine learning for object recognition and identification and for the learning of complex beheaviours.

The limitation is -it's a bit technical, but basically, in principle, machine learning is possible under certain assumptions, as laid out by Valiant in his PAC-learning paper (A Theory of the Learnable), especially the assumption that a training sample will have the same distribution as unseen data. Under this condition, machine learning can be said to work and we can look at performance metrics and be happy they look good.

Well, except that the real world has no obligation to operate under our experimental assumptions, so once you deploy machine learning systems in the real world, their performance goes down, because you haven't seen nearly enough of the data you really need to see, in the lab.

And, if you attach such assumptions to safety-critical systems, then you're taking an unknown and unquantifiable risk. Or in other words, you're putting peoples' lives in danger.

And that's everyone who uses machine learning to train cars to drive in real-world conditions. Not just Uber.

Re: Tempe Police Release Video of Uber Accident

#910
post #136

Earlier quoted context omitted.

> The gap between street lights (and hence the person) was in the field of view of the camera the entire time But the gap between street lights is going to be very hard to see into. > I'm confident my eyes are good enough that I would have been able to see this person at night in these lighting conditions. I think you're overconfident. Human low light vision is very good if there is low light everywhere. But it is no…

> But the gap between street lights is going to be very hard to see into. Looking, right now, at a parking lot between two lights from a well-lit room. I can make out most of the outline of the black car in the middle of the "darkness" without any trouble. This isn't even the low light vision kicking in (which I agree isn't going to kick in if you're driving). Human vision should be able to make out the pedestrian ea…

This street in particular is weird at night because the street downstream rises up, and the light from those lamps is cast at a higher point. The place she was hit is extremely dangerous because there are no lights on her, and no lights behind her.
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