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Comment by WilTimSon | Hacker News Reader

Wow, I never actually stopped to think about the way Google determines traffic but it seems so obvious now. This is a very simple but cool trick, I'd expect to see something like this in an action movie where people need to reroute an important car to a particular street.

Anyone have any idea how often this data is updated? So if the guy runs through a street with a cart and it turns red, when will it show up as clear?

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I guess an important piece (conveniently left out of this story) is that it does not work if there are other cars on the road, as these cars quickly invalidate the data coming from the slow cart.

But wouldn't that other car be classified as error?

I don't know what the tipping point is, but it'd probably take more than one. I've commuted through backed up/stopped/solid red sections on a motorcycle where I just get to lane-split and cruise through, and it'd still stay red.

I think Google uses phone sensors to tell motorbikes apart form cars. Pretty simple tech: cars don't lean.

Which makes it all the more infuriating that Google Maps still has huge flaws when it comes to motorbike navigation.

> I think Google uses phone sensors to tell motorbikes apart form cars

While they could, I doubt they do... do you have evidence of this?

not the GP, and I don't how it's done, but my Google Maps timeline does distinguish between motorcycling and car trips, however its reliability is questionable. It has often mis-categorised my motorcycle trips as car trips, but rarely if ever the reverse.

I would guess (unsubstantiated) that it classifies a motorcycle trip as being unexpectedly fast through many traffic jams.

They are pretty good to identify public transit from cars too.

I always assumed an average was performed over instantaneous velocity that fall in network segments. So, it would depend on the relative magnitude and the edge count on the graph in question you wanted to manipulate.

For a long very straight road represented as a single edge, I would assume if you had 100 actual cars, you'd get an average of the manipulated data rate and the real flow rate.

It works out to the same thing, more or less, but I'd guessed they used proximity nodes (junctions) and then when you reach another node use the time (discounting outliers).

Then do the calculations at the server for speed and such.

Not sure if a few cars with GoogleMaps users would cancel out the data from 100 smartphones in the cart though.

Just add more smartphones to the cart and those other cars will be considered the error.

I was going through an empty road in an empty area (no buildings nearby) in the middle of the night, and somehow it's red on google map. Turns out there was a single car stopping on the side of the road, and that's enough to make google maps think there was a congestion there. As soon as I passed the car, the road is green again.

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