[leokeba]

If the developers are around, I would like to ask a simple question : Does this app only use realtime data for calculating ETA and routes, or does it learn some statistical regularities in the traffic patterns to make predictions ?

I'm asking because this is the main weakness of all similar apps that I know of, they always give you an estimation using only the current state of traffic on the whole journey, so if you are going towards a busy city at peak traffic time it may add one or two hours to the ETA even if you are still 5 hours away and everything will be gone by the time you get there. Obviously the reverse situation is even more annoying, I live in the Paris area, and when I leave home around 4pm and ask google maps an itinerary, it may tell me I'm only 30 minutes away, but 15 minutes later shit hits the fan and I end up an hour late on my schedule.

Obviously after a while you start learning the traffic patterns and plan accordingly, which is okay I guess, but we're in 2023, how can google not be up to the task of correctly predicting a traffic spike when it's regular on a daily or weekly basis ? Is that just too much data / compute for them ? If anybody has a clue, I'm curious.

[PcChip]

I thought the "arrive at" feature of Google maps took into account usual traffic patterns at that time of day?

[alistairSH]

In theory.

However it appears to underestimate traffic delays for DC->OBX beach traffic. On a summer Saturday morning, that’s a 6-7 hour drive. Or worse. Apple Maps has it closer to 5-5:30 for most of the day. Google gives a range from 4:45-6:30 - 4:45 is basically impossible any time of day and year but 6:30 is ballpark-ish if you don’t hit a major traffic jam.

But maybe that’s a worst-case route.

[leokeba]

Well that's also what I used to believe, kinda makes sense. But drawing from my own anecdotal experience I had to conclude that's not the case. Maybe I'm wrong, and it's just VERY bad at it, or it doesn't work where I live.