Very much agree, with only one caveat: unpaved roads.
Google Maps estimates are wildly off when parts of the drive are along unpaved roads in Australia. It assumes a ludicrously low speed of 30-40 km/h for such roads, when most cars are able to go 80+ km/h, depending on the road. I've beaten Google arrival estimates by more than 2 hours on some drives.
When planning drives involving unpaved sections, we usually ask Google for the estimates for the paved sections (which are generally accurate), then estimate the unpaved sections based on the distance and a guess at a reasonable speed for the road.
I've also noticed that Google is much better at estimating speeds along unpaved roads that have mobile signal coverage. It seems like it uses user-generated driving data for them to some extent, but not at all for the ones without coverage. This leads me to think that they accept real-time user data, but will not "queue" the gathered data on the app for uploading later, when mobile signal is available.
This seems like a strange decision, given that unpaved roads and lack of mobile coverage correlate by nature. I suppose it's probably a security-minded decision, to prevent malicious agents from easily uploading bad data. Or maybe a quirk of the way Waze data plays into this.
One (totally unverified, bu) hypothesis that I have is that they drastically underestimate speed on roads that are rarely used by cars but frequently used by farming vehicles; they're using user data to estimate the speeds, they can see that the 'usual' vehicle going there is driving 30 kph but they can't see that it's a tractor pulling a wagon of hay.
Interestingly enough i was really surprised when i used Gmaps in Thailand and Cambodia with the exact same issue of bad roads. It was usually accurate. However i think i always had cell signal so your assumption likely is right.
It's not just unpaved roads. I also find that "private" roads (inside gated communities) around me are often extremely far off in terms of speed limit. There are private roads around here with speed limits of 45+ MPH that Google seems to calculate as 15-25MPH. It really throws off the time estimates if you're coming from or going to one of those neighborhoods. And it's been like that for YEARS. If they were using user-generated data, I'd expect that it would eventually get better, but I've seen no evidence of it. Waze does a better job at this.
I don't think the paving has as much to do with this as the smartphone traffic. I find drives on rural paved roads with no cell reception and low population are often overestimated by 30%. Maybe I drive too fast on these roads. I certainly appreciate Google keeping other drivers off these roads, however.
Google Maps estimates are wildly off when parts of the drive are along unpaved roads in Australia. It assumes a ludicrously low speed of 30-40 km/h for such roads, when most cars are able to go 80+ km/h, depending on the road. I've beaten Google arrival estimates by more than 2 hours on some drives.
When planning drives involving unpaved sections, we usually ask Google for the estimates for the paved sections (which are generally accurate), then estimate the unpaved sections based on the distance and a guess at a reasonable speed for the road.
I've also noticed that Google is much better at estimating speeds along unpaved roads that have mobile signal coverage. It seems like it uses user-generated driving data for them to some extent, but not at all for the ones without coverage. This leads me to think that they accept real-time user data, but will not "queue" the gathered data on the app for uploading later, when mobile signal is available.
This seems like a strange decision, given that unpaved roads and lack of mobile coverage correlate by nature. I suppose it's probably a security-minded decision, to prevent malicious agents from easily uploading bad data. Or maybe a quirk of the way Waze data plays into this.