I ran into this problem a lot when I was living in downtown SF of all places. One should never drive in front of AT&T/Oracle stadium when an event is ending, as the traffic is insane and part of the road is closed to allow for the mass of pedestrians. But Maps interprets pedestrian traffic as car traffic and shows that section of the road as green and moving faster than the sections with actual cars, and tries to direct you down it.

Reminds me of the fellow who tried forcing it to think traffic was bad by dragging a cart full of cell phones down the road slowly

Obviously we need to have Google connect our cars to the internet so they have more data points. And we also need Google to connect our bikes to the internet, that way Google can tell the different between a bike and a car. And we need to prevent the bike from being able to be used if the Google tech isn't charged and working, because it would be dangerous for everyone else if Google thought that person was in a car and not a bike.

You jest, but in time this will be true, not because of Google, but insurance requirements. Same for autonomous cars. You would still be able to drive your car yourself, if you can afford the insurance, and you won't.

> How does Google tell the difference between someone on an electric bike vs a car

With all the sensors in the phone, it is not that hard. There's a lot of research in that field...

I couldn't find a paper that talks about the specifics of this very problem. The ones I've found in the past fail with outliers like a bike going through stopped traffic and or the scenario above.

The best approach I could think of is they expand the time they're looking at to classify the vehicles before the outlier situations.

I believe you can get a lot of information from accelerometer data. Especially when compared with other data for the same road. Is it even used in this way?