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281 points nharada | 1 comments | | HN request time: 0.292s | source
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NullHypothesist ◴[] No.45902077[source]
This is a huge sign of confidence that they think they can do this safely and at scale... Freeways might appear "easy" on the surface, but there are all sorts of long tail edge-cases that make them insanely tricky to do confidently without a driver. This will unlock a lot for them with all of the smaller US cities (where highways are essential) they've announced plans for over the next year or so.
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embedding-shape ◴[] No.45902557[source]
> Freeways might appear "easy" on the surface, but there are all sorts of long tail edge-cases that make them insanely tricky to do confidently without a driver

Maybe my memory is failing me, but I seem to remember people saying the exact opposite here on HN when Tesla first announced/showed off their "self-driving but not really self-driving" features, saying it'll be very easy to get working on the highways, but then everything else is the tricky stuff.

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xnx ◴[] No.45902725[source]
Highways are on average a much more structured and consistent environment, but every single weird thing (pedestrians, animals, debris, flooding) that occurs on streets also happens on highways. When you're doing as many trips and miles as Waymo, once-in-a-lifetime exceptions happen every day.

On highways the kinetic energy is much greater (Waymo's reaction time is superhuman, but the car can't brake any harder.) and there isn't the option to fail safe (stop in place) like their is on normal roads.

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GloamingNiblets ◴[] No.45903461[source]
I don't have any specific knowledge about Waymo's stack, but I can confidently say Waymo's reaction time is likely poorer than an attentive human. By the time sensor data makes it through the perception stack, prediction/planning stack, and back to the controls stack, you're likely looking at >500ms. Waymos have the advantage of consistency though (they never text and drive).
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1. viftodi ◴[] No.45904193[source]
Even if we assume this to be true, waymos have the advantage of more sensors and less blind spots.

Unlike humans they can also sense what's behind the car or other spots not directly visible to a human. They can also measure distance very precisely due to lidars (and perhaps radars too?)

A human reacts to the red light when a car breaks, without that it will take you way more time due to stereo vision to realize that a car ahead was getting closer to you.

And I am pretty sure when the car detects certain obstacles fast approaching at certain distances, or if a car ahesd of you stopped suddenly or deer jumped or w/e it breaks directly it doesn't need neural networks processing those are probably low level failsafes that are very fast to compute and definitely faster than what a human could react to