It's a privacy issue to use that kind of data, because the employees who build the map shouldn't be looking at one guys GPS traces. So instead the traces are cut into tiny chunks and aggregated and only shown where there are more than 50 people at the same spot. That effectively means there is no data available to make decisions on the most rarely used roads.
Also, even if they choose to not do this for maps even though they do it for lots of other things, merely aggregate traffic info on roads would be useful. 364 days of zero traffic and one day with 30 minutes of one car would be useful.
The same algo that does that could tell the field mapper to go look at roads that are barely used (or whatever criteria ends up being the best), it doesn't need to tell them how many people or who went on that road.
Sometimes I think that Google create their road maps solely using satellite pictures.
How does Google tell the difference between someone on an electric bike vs a car going on a dirt road doing 20-30km/h to not have rocks flying everywhere?
With all the sensors in the phone, it is not that hard. There's a lot of research in that field...
The best approach I could think of is they expand the time they're looking at to classify the vehicles before the outlier situations.