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This is looking at it all wrong. Watch Chris Urmson's video from SXSW on how Waymo does it. I've mentioned that before. You build a map of what's around the vehicle. Then you try to tag some obstacles to help predict their behavior. But the obstacle detection is geometric, and does not depend on the tagging, which uses machine learning. If there's an obstacle, the system doesn't hit it, even if it has no clue how to identify it.

Tesla/Mobileye managed to get that backwards. Their original system was "recognize vehicle visually, compute distance and closing rate to vehicle". If it didn't recognize an obstacle as a vehicle, it ignored it. We know this for sure, because you can buy a Mobileye unit as a dashcam-like warning device and many people have seen how they work. That led to three collisions with vehicles partly blocking the left side of a lane. One death ramming a street sweeper, one collision with a stopped fire truck, one sideswipe. The NTSB is investigating the fire truck collision.

The NTSB is now investigating the Uber collision.[1] As they usually do, the first thing they did was to get control of the wreckage.[2] Uber does not have control of the investigation. The NTSB investigators are working this like an air crash. They are "beginning collection of any and all electronic data stored on the test vehicle or transmitted to Uber". As usual, they haven't announced much, but they have mentioned that the video seen publicly is from a third-party dashcam, not the vehicle sensors.

[1] https://www.ntsb.gov/news/press-releases/Pages/NR20180320.as...

[2] http://wsau.com/news/articles/2018/mar/21/arizona-police-rel...




Devils advocate here, but what if a supposed “obstacle” is a plastic bag or a jet of steam coming out of a sewer grate?


Then you add special cases for steam, and plastic bags, and small fast moving animals that it's more dangerous to swerve around than hit. And then when some kid in a chicken costume runs out in front of the car, the car stops even though it can't identify exactly what it's looking at.


Then you stop. Type 2 errors for cars are much less dangerous than Type 1 errors.


Unless it’s icy out, you have to swerve, or you’re being tailgated...but yes, stopping (or at least attempting to stop) is the best decision from a liability perspective.


Well that's when you're grateful that along with your forward collision prevention, your car's ABS and electronic stability control systems are also still enabled.

As for tailgating, this seems to be a problem with U.S. attitudes, not vehicle mechanics. Stop making it acceptable to tailgate! If you're close enough to the vehicle in front of you that any significant braking on its part will cause you to hit it you are too close and it's your fault if you hit it.


Isn't that the case in the US? In the EU, you can be fined for driving too close to the car in front of you.

I think that driving close to the car in front of you is the number 1 cause of accidents. Much more dangerous than driving fast.


Legally, in most (if not all) of the US you /can/ be cited for tailgating (the laws require a minimum following distance).

Reality is that the traffic cops seldom ever cite for tailgating in general. If one were to see a citation for such, it is likely after an accident where the officer can deduce that the cause was "following too closely" and so they then issue the citation.


In Australia, if you are the rear vehicle in a rear-end accident you are automatically at fault in almost all circumstances. The only exceptions I know of are if the front car pulled out immediately in front of the rear car, or if the front car was reversing.


> I've mentioned that before. You build a map of what's around the vehicle.

If it were that easy, everyone would have solved it already. Detecting distances, objects etc. from several varied sensors is exactly how you build this map. You can't just handwave the map into existence.




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