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Is it just me or does whitelisting static objects to determine whether the car will collide with them seem like a bit of a crude hack? It almost sounds like the
by karyon 10y ago
Is it just me or does whitelisting static objects to determine whether the car will collide with them seem like a bit of a crude hack? It almost sounds like the system will brake at newly installed traffic signs.
edit: Upon closer reading, he explains it somewhat. Once they have enough data, the system will start braking on unknown objects with gradually increasing force as the confidence level rises. So basically, it will brake on unknown traffic signs but only slightly, as the confidence level shouldn't get too high, if I understand that correctly.
The last paragraph sounds technically challenging and interesting:
"Taking this one step further, a Tesla will also be able to bounce the radar signal under a vehicle in front - using the radar pulse signature and photon time of flight to distinguish the signal - and still brake even when trailing a car that is opaque to both vision and radar. The car in front might hit the UFO in dense fog, but the Tesla will not."
edit: it seems like they are already doing it beginning with this update: "Now controls for two cars ahead using radar echo, improving cut-out response and reaction time to otherwise-invisible heavy braking events". that sounds awesome.
- CaveTech 10y agoI think you have it backwards. The radar will not initiate braking events for newly discovered stationary objects. Once it has human feedback from multiple sources, the object will be whitelisted and cause braking events. blacklisting would cause the behaviour you describe.
- lorenzhs 10y agoI read it the same way as karyon. Whitelisting something means recognising it in a known-good way (in this case, "we know that's an overhead sign"), whereas blacklisting means known-bad.
- karyon 10y agoThe blog post says "When the car is approaching an overhead highway road sign positioned on a rise in the road or a bridge where the road dips underneath, this often looks like a collision course. [...] If several cars drive safely past a given radar object, whether Autopilot is turned on or off, then that object is added to the geocoded whitelist." So as i read it, the system does think it will collide but ignore it if the whitelist says the object is safe. The paragraph after that says basically once they have enough data, the system will start braking on unknown objects with gradually increasing force as the confidence level rises. So basically, it will brake on unknown traffic signs but only slightly, as the confidence level shouldn't get too high.
- Animats 10y agoBasic problem: the system doesn't know where the road surface is. Google's vehicles, and most of the DARPA Grand Challenge off-road vehicles, profiled terrain with a LIDAR. They know where the road surface is. This is essential to off-road operation, but on-road, optimistic assumptions (no big potholes, road not leading off cliff) can be used, at some risk.
- source99 10y agoWhat about a tractor trailer (like Florida) in the same spot as a white listed traffic sign?
- manicdee 10y agoRoad signs will be more to the left or right, truck will be in front. Corner case: truck jackknifed across the road immediately under a white listed gantry.
- manicdee 10y agoI read this as saying: we start braking lightly when detecting an unknown object, applying more braking force as it becomes clearer that this object is a collision risk. Once enough human or autopilot trips detect the same signal with no collision, whitelist the signal and cease braking-and-monitoring behaviour. I am probably misinterpreting but that is what makes sense to me.
- MarcelGerber 10y agoYes, this seems really complex to me, too. I'm also not quite sure on why exactly it is so complex to distinguish between objects (including vehicles) on the road and ones above/next to it. If they have radar images (I imagine them as images with depth information, which might be fundamentally wrong), they should be able to tell both where the road is going and, with that information, which of these objects are of relevance. But for the learning part, they probably combine the camera that they used to date as their primary device in combination with the radar (at least in daylight scenarios) to identify objects. They may even be able to learn about the special material properties, like the reflective coating of a traffic sign.
- toomuchtodo 10y ago> I'm also not quite sure on why exactly it is so complex to distinguish between objects (including vehicles) on the road and ones above/next to it. Because radar does not have the same resolution as LIDAR. EDIT: Phased array radar and cheap stationary LIDAR should get under $100 in ~5 years, at which point this whole argument will be moot. Hacks in the meantime!
- Pyxl101 10y agoWhat does the world look like in radar? Are there any visualizations available? Could multiple radar emitters and receivers be used to create a phased array and improve resolution?
- danielmorozoff 10y agoHere is the resolution calculation for aircraft radar (with respective example of signature - aka image ) http://www.radartutorial.eu/01.basics/Range%20Resolution.en.html http://www.radartutorial.eu/01.basics/Range%20Resolution.en.... For angular resolution: http://www.radartutorial.eu/01.basics/Angular%20Resolution.en.html http://www.radartutorial.eu/01.basics/Angular%20Resolution.e...
- wyager 10y ago> What does the world look like in radar? Depends on the radar system. Some are distance only without direction. Some are 1D (a line, usually horizontal) and some are 2D. Many objects are partially opaque, which is confusing. Resolution is very poor compared an optical device of the same size. > Could multiple radar emitters and receivers be used to create a phased array and improve resolution? Yes. However, this is currently bulky and expensive (in dollars and in compute power). Thankfully, it looks like capitalism is coming in to the rescue here and miniaturizing the everloving shit out of complex radar arrays for human interface tech. This should be usable for vehicles as well.
- hexane360 10y ago>It almost sounds like the system will brake at newly installed traffic signs. One of the only situations where both "brake" and "break" have the same meaning in a sentence.
- limaoscarjuliet 10y agoOr, worse yet, will crash into an actual obstacle where white listed sign is.
- T0T0R0 10y agoUpon closer reading, he explains it somewhat. The author of the article is a nameless collective, not an individual. They explain it, but there is no "he" to ascribe the explanation to. We do not know the names of the authors.
- alanh 10y agoAnnoying you are being downvoted. You are entirely correct, and it is worthwhile to fight against the nonsensical notion that Elon === Tesla.
- Cogito 10y agoFor what it's worth, there is some strong evidence that Elon penned this post himself - not that it is clear from the post itself. https://twitter.com/elonmusk/status/771446048262946816 https://twitter.com/elonmusk/status/771446048262946816 > Finishing Autopilot blog postponed to end of weekend https://twitter.com/elonmusk/status/774155658476212224 https://twitter.com/elonmusk/status/774155658476212224 > Will get back to Autopilot update blog tomorrow. https://twitter.com/elonmusk/status/774664927835553792 https://twitter.com/elonmusk/status/774664927835553792 > Will do some press Q&A on Autopilot post at 11am PDT tmrw and then publish at noon. Sorry about delay. Unusually difficult couple of weeks.
- alanh 10y agoI was already aware of these tweets, but that doesn’t mean he wrote it all himself, just that he is involved in it. The fact is, the blog post has a byline and the byline does not mention Elon Musk or any individual person's name.
- karyon 10y agoI got this from twitter, where Elon Musk writes stuff like "Writing post now with details." and "Will get back to Autopilot update blog tomorrow." So I assumed he's authored the thing.
- NamTaf 10y agoYup. As soon as you're white/blacklisting you've lost at AI because you're assuming the rules never change, and if that's the case then why use a learning AI in the first place. I wonder how many fatalities it'll take before they realise that 'the driver should've been paying attention' isn't a good enough excuse.
- manicdee 10y agoIncremental steps. They will move past whitelisting in time. Note that humans use whitelisting too, to the point that they do not notice when a stop sign has been defaced or converted to a "give way".
- indolering 10y agoSelf-driving cars are entirely reliant upon mapping data for all sorts of functionality. For example, how is it supposed to differentiate between curved roads and on/off ramps? Decent navigational maps require huge amounts of manual intervention, which is why Apple's mapping software initially sucked. The maps for self-driving cars will require an order-of-magnitude more data.
- lnanek2 10y agoYes, but Apple and Google, they only have what their company cars bring in for road data. Tesla makes it clear every customer is also acquiring data for all their cars to make better decisions: > Curve speed adaptation now uses fleet-learned roadway curvature So they have an advantage over Google and Apple in that they have mass market cars full of sensors being driven for them for free.
- kccqzy 10y agoApple and Google have billions of smartphones collecting location data. Not all of the data are currently sent back, but they can certainly do it with just a software update. For example on my iPhone under location services it already lists "routing & traffic" as one of the system services using location. It's easy enough to extend it to mapping too.
- viraptor 10y agoUnfortunately that's only location data. What cars with more sensors can send is closer to: this location has N lanes, turning radius is M, the slope is X, I'm travelling at Y mph, I see connected road at location Z, I see the following signs... What your phone can send is only "I'm more or less at X, I'm moving fast so we may be in a car. But I may as well be in a glider. Who knows..."
- indolering 10y agoI guess so... Google's mapping cars have expensive sensors that won't make it into production cars. And if they partner with a single auto manufacturer or buy up Lyft, they will have just as much data as Tesla has.