As someone who lives on a residential street right by a primary school in the UK, the majority of drivers are going over 20mph even at the peak time when there are children everywhere.

While in theory human drivers should be situationally aware of the higher risks of children being around, the reality is that the majority will be in their own bubble of being late to drop their kid off and searching for the first free spot they can find.

Your opinion of "most humans" is vastly overinflated. The median human driver would be going 5 over the speed limit, on their cell phone, and paying fuck all attention. Humans never drive as slow as 17 mph, even in the context of being directly in front of schools with visible children.

> But most humans would have been aware of the big picture scenario much earlier.

I wouldn't call it likely. Sure, there are definitely human drivers who are better than Waymo, but IME they're few and far between. Much more common to be distracted or careless.

Have you been in a waymo? It knows when there are pedestrians around (it can often see over the top of parked cars) and it is very cautious when there are people near the road and it frequently slows down.

I have no idea what happened here but in my experience of taking waymos in SF, they are very cautious and I'd struggle to imagine them speeding through an area with lots of pedestrians milling around. The fact that it was going 17mph at the time makes me think it was already in "caution mode". Sounds like this was something of a "worst case" scenario and another meter or 2 and it would have stopped in time.

I think with humans, even if the driver is 100% paying attention and eyes were looking in exactly the right place where the child emerged at the right time, there is still reaction times - both in cognition but also physically moving the leg to press the pedal. I suspect that a waymo will out-react a human basically 100% of the time, and apply full braking force within a few 10s of milliseconds and well before a human has even begun to move their leg.

According to the article the car was traveling at 17 miles an hour before it began braking. Presumably this was in a 25 mph school zone, so it seems the Waymo was already doing exactly what you describe - slowing down preemptively.

It would be nice to see the video (although maybe there are some privacy issues, it is at a school after all).

Anyway, from the article,

> According to the NHTSA, the accident occurred “within two blocks” of the elementary school “during normal school drop off hours.” The safety regulator said “there were other children, a crossing guard, and several double-parked vehicles in the vicinity.”

So I mean, it is hard to speculate. Probably Waymo was being reasonably prudent. But we should note that this description isn’t incompatible with being literally in an area where the kids are leaving their parents’ cars (the presence of “several double parked cars brings this to mind). If that’s the case, it might make sense to consider an even-safer mode for active student unloading areas. This seems like the sort of social context that humans might have and cars might be missing.

But things speculation. It would be good to see a video.

In this situation, the car was already driving under the legal speed required for a school zone (25mph when children are present) [edit: some comments in the post suggest there is a 15mph sign, which is sometimes posted; to me, driving 17mph in a 15mph zone is acceptable).

I think any fair evaluation of this (once the data was available) would conclude that Waymo was taking reasonable precautions.

It was going 17 mph. That is rather slow.

To put it another way. If an autonomous vehicle has a reaction time of 0.3 seconds, the stopping distance from 17 mph is about the same as a fully alert human driver (1 second reaction time) driving 10.33 mph.

> The car only slows down after seeing someone.

How do you know that? The article says it slowed from 17 mph. That’s cautious progress speed, not cruising speed.

Two things:

I've read studies saying that most drivers don't brake at max effort, even to avoid a collision. This may be at least one of the reasons that Waymo predicted that an attentive human would likely have been going faster than their car at the moment of impact. I've got a good idea of my fun-car's braking performance, because I drive it hard sometimes, but after reading that I started practicing a bit with my wife's car on the school run, and... Yeah: it's got a lot more braking power than I realized. (Don't worry, I brake hard on a long straight exit ramp, when no one's behind me, a fast slow-down is perfectly safe, and the kiddo loves it.) I've now got an intuitive feel for where the ABS will kick in, and exactly what kind of stopping distance I have to work with, which makes me feel like a safer driver.

Second, going off my experience of hundreds and hundreds of ride-share rides, and maybe thirty Waymo journeys, I'd call the best 10-15% of humans better drivers than Waymo. Like, they're looking further up the road to predict which lane to be in, based on, say, that bus two blocks away. They also drive faster than Waymos do, without a perceptual decrease in safety. (I realize "perceptual" is doing some work in that sentence!) That's the type of defensive and anticipatory urban driver I try to be, so I notice when it's done well. Waymo, though, is flat-out better, in every way, than the vast majority of the ride-share drivers I see. I'm at the point where I'll choose a Waymo any time it'll go where I'm headed. This story reinforces that choice for me.

Curiously enough Google could have access to how fast humans usually drive through that street.. if they record people's Google Maps trips, they can show the court that "Look, 80% of Google Maps users drive through here at 30 mph!".

I live in an area where there are pedestrians stepping into the street without looking, all over the place, and you can drive / cycle without hitting them but have to slow down appropriately if you have to go near something that you can't see behind. Like you say it would be interesting to see the video.

> But most humans would have been aware of the big picture scenario much earlier. Are there muliple kids milling around on the sidewalk? Near a school? Is there a big truck/SUV parked there?

Waymos do this and have for years. They know where the people are around them and will take precautionary action based on that.

Here's a video from 2019 of one understanding that a car in the bike lane means the cyclists may dart out into the lane it's in and taking action based on that. https://waymo.com/blog/2019/05/safety-at-waymo-self-driving-...

That video is nearly 7 years old at this point and they've gotten much, much better since then.

If you think a fully-attentive human driver would have done better, I think you're kidding yourself.

I know you didn't make this point, but if anyone think the average LA driver would have done better than this I've got a bridge to sell you and that's really what matters more. (I say that as someone who used to live like half a mile from where this happened)

There's a bus stop right behind my house. I routinely hear the driver honking and yelling at people who ignore when the stop sign is extended (which is a misdemeanor in my state). So forgive me for not assuming a human would have done better.

I drive like this too, but I think we’re a small minority. Especially here in LA.

It was already moving slowly. 17MPH is pretty conservative. Most human drivers going past my local school are doing at least 30.

In principle, attentive drivers, who have either somehow come independently to the appropriate understanding or have been trained in how to react to hazards ahead...

https://www.gov.uk/theory-test/hazard-perception-test

... could in some circumstances know that there's a likelihood that a child will emerge suddenly and reduce their speed in anticipation where circumstances allow.

Note that: If you cut speed but other drivers can't see why they may overtake, even unsafely, because you are a nuisance to them. Slowing in anticipation that a child will run out from behind the SUV, only for a car behind you to accelerate around you and smack straight into the child at even higher speed, is not the desired outcome even though you didn't hurt anybody...

And yes, we'd need to see the video to know. It's like that Sully scenario. In a prepared test skilled pilots were indeed able to divert and land, but Sully wasn't prepared for a test. You're trained to expect engine failure in an aeroplane - it will happen sometimes so you must assume that, but for a jet liner you don't anticipate losing both engines, that doesn't happen. There's "Obviously that child is going in the road" and "Where the fuck did they come from?" and a lot in between and we're unlikely to ever know for sure.

> But most humans would have been aware of the big picture scenario much earlier. Are there muliple kids milling around on the sidewalk? Near a school? Is there a big truck/SUV parked there?

Waymos constantly track pedestrians nearby, you can see it on the status screen if you ride in one. So it would be both better able to find pedestrians and react as soon as one was on a collision course. They have a bit more visibility than humans do due to the sensor placement, so they also can see things that aren't that visible to a person inside the car, not to mention being constantly aware of all 360 degrees.

While I suppose that in theory, a sufficiently paranoid human might outdo the robot, it looks to me like it's already well above the median here.

Are they not using a ton of ML to take exactly this sort of context into account?

>The car can react faster that I can after seeing someone

and that can potentially allow internal planning algorithm to choose more risky and aggressive trajectories/behavior, etc. say to reach target destination faster and thus deliver higher satisfaction to the passengers.

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Precisely. Environmental context is not considered in Waymo's "peer-reviewed model" (I encourage reflexive commenters to first read it: https://waymo.com/safety/collision-avoidance-benchmarking), only basic driver behavior and traffic signal timings.

Note the weaselly "immediately detected the individual as soon as they began to emerge" in the puff piece from Waymo Comms. No indication that they intend to account for environmental context going forward.

If they already do this, why isn't it factored in the model?