Uber gaslit me with its ETA and all I got was gridlock and a missed train.
I don’t use Uber often, but when I do, it’s usually for a time-sensitive trip: a train station, an airport, somewhere I can’t afford to be late…which I recently learned is probably not the best use case…
Last week, I missed my train after an Uber ride took double the time estimated. I live about six miles from the station, a straight shot down the main road. It’s normally a twenty minute drive. But that day, Google Maps, Apple Maps, and Waze all showed that main road as deep red due to construction, congestion, and the sticky sluggishness of summer. Luckily, the maps also showed ample alternate routes – a brief detour on the interstate, for example, could keep the trip to its usual twenty minutes.
When I booked my Uber, the app confidently asserted that I’d be at the station in exactly twenty minutes, a comfy fifteen minutes before my train’s departure time.
Perfect, I thought. Uber’s *elite* GPS knows the best way to route around the traffic.
Except! It doesn’t. The driver’s in-app GPS sent us straight into the most congested road, the exact one the other apps had warned against. Yet Uber’s ETA remained unchanged.
As I sat at a standstill, I clung to the idea that maybe Uber had cracked something the other navigation giants hadn’t. This was a company with the resources to build its own routing engine – surely their billion-dollar infrastructure had spotted a coming break in traffic the other apps hadn’t caught yet?
Nope. As my ETA came and passed, the app began revising my arrival time in painful minute-by-minute increments, all the way until I finally arrived at my destination with the train long departed from the platform.
What the heck? Why did Uber’s navigation system do that?
I felt compelled to report this issue to Uber, my naive mind imagining a product team eager to troubleshoot a potential flaw in their pride of a proprietary navigation system. After all, in a 2015 blog post, Uber’s engineering team did brag about the accuracy of their technology. “Ultra-efficient route planning and highly accurate ETAs are critical“, they said.
In spite of this, every customer service channel shut down my attempt to escalate, offering nothing beyond the canned line: “We are working towards improving ETA accuracy.” A few responses reiterated Uber’s five-minute grace period to cancel a ride for free, as if that had anything to do with the problem at hand. It began to seem like this was a issue that Uber’s support team was probably trained to deflect and contain.
After digging deeper, I found that Uber’s subpar GPS was in fact a known and widely reported issue by drivers and riders alike, with complaints going as far back as 2014 when Uber first rolled it out with the promise of getting riders to their destination “via the best possible route,” as stated in a press release at the time.
“The [new] Uber navigation is quite poor. It often suggests a bad route” an early user reported in 2014.
Over a decade later, it seems like not much has changed. In a recent post on r/uber titled “Why is the Uber GPS so bad?“, the OP said: “The GPS always gives my drivers the worst routes.” On RideGuru, a driver shared that Uber’s GPS sent them “in circles”, but switching to Waze found the destination “right away”. A Redditor on r/uberdrivers explained: “If you’re using Uber GPS … they’ll make you take the shortest route even if it takes much longer, then pocket the difference on their flat-rate trip.” Another Redditor added bluntly: “The algorithm was set to lowball drivers as much as possible.”
Before rolling out their own system, Uber relied on Google Maps for routing (which Lyft still uses today). But Google’s API fees, combined with a well-publicized feud between the companies pushed Uber to invest in its own navigation system. Today, from what I can gather, Uber’s routing engine is a hybrid stack of global street data coupled with open map database to fill coverage gaps, as well as third-party imagery and geocoding services to enhance accuracy.
What’s missing? Leading navigation apps all ingest traffic data from millions of devices and live incident reports, updating routes in near real time. Uber’s data comes primarily from its own insulated database of trips, a smaller and less continuous dataset. Traffic updates may only come periodically and from fewer data sources, making Uber’s routing service slower to reroute around unseen congestion.
Ahh, I think back to an airport trip a few years ago when Uber routed my driver to drive straight into a construction site… where a street used to be. Makes sense now.
So, why, after 10+ years of complaints from riders and drivers alike, is Uber’s strategy to smother the issue as quickly as possible? Do we even get a strategic PR response?
Probably not.
There isn’t really a compelling business case to change it.
Uber’s routing technology was probably never built to prioritize accuracy. Its algorithms likely balance multiple incentives like trip acceptance rates, driver pay structures, and overall platform efficiency. For example, if an inaccurate but optimistic ETA nudges riders to book faster or drivers to accept more trips, then that could be seen as a success factor from a business standpoint, one that would compensate for any business cases to recalibrate toward more realistic arrival times.
Because the system leans heavily on its own proprietary data, it probably suffers from something known as algorithmic inertia. Instead of drawing on the vast, real-time traffic datasets that power leading navigation apps, Uber’s navigation learns from the routes its own drivers have historically taken. If a particular path was used a lot in the past, the model likely treats that route as “high-confidence” simply because it has the most trip history behind it. Over time, that reinforces the same routing decisions, good or bad, locking the system into its own feedback loop.
Despite years of complaints, the issue of mapping accuracy doesn’t seem like it’s gained enough traction to sway Uber’s drivers or customers toward competitors. And Uber spends only about 1% of its revenue on platform R&D, which seems rather low for a tech giant. But the message is clear. Uber is perfectly happy with its scotch tape of a navigation system.
Anyway, when the routing feels slow, most riders blame the driver, not the platform. It’s the perfect setup for the tech-centered “share economy”: the platform keeps its margins, the worker takes the heat. But that’s a topic for another post.