11–20 of 20 posts
Why do they need a 3d map to begin with? Following their example of which side of the canyon the phone is, given the snr of sat b,c,d they can guess the side of the street. If it's possible then being shadowed by an actual building, a construction site or a delivery truck amounts to the same result (but I guess the snr would vary between these 3 situations). Hence, why the need for the 3d model?
A big problem with Uber/Lyft is that drivers take all these fancy calculated positions and plug them into a standard navigation app, which can direct the driver to the completely wrong side of a large block. (Addresses are not very granular in a city.) It’s interesting to me why Uber/Lyft allow this.
A big problem with Uber/Lyft is that drivers take all these fancy calculated positions and plug them into a standard navigation app, which can direct the driver to the completely wrong side of a large block. (Addresses are not very granular in a city.) It’s interesting to me why Uber/Lyft allow this.
I have tried to contact Google and get this fixed at least a dozen times over the past decade, always ignored. They used to have a whole community mapping thing where you could submit issues with the map, but those apparently are ignored.
It's a real nightmare trying to convince the insurance company and local government that google is wrong, love how that's my responsibility too.
I mostly use Lyft now because I was tired of fighting with the Uber app to get it to show my correct location
> The use of particle filters necessitates a level of server affinity. Each new request to our service must be routed to the same back-end server for processing in order to update the correct particle filter. Was implementing this on the client device considered? What were the motivations for this design?
1. Building 3D data is too large or inconvenient to store on the device.
2. Continuously downloading/caching small localized chunks of that data would result in unacceptable use of bandwidth for customers with limited data plans.
3. Their implementation of the algorithm may be CPU inefficient and contribute to excessive battery drain.
4. (cynical) This gives them yet another excuse to be sucking up and storing 1Hz precise user location data, potentially to use for other reasons...
A big problem with Uber/Lyft is that drivers take all these fancy calculated positions and plug them into a standard navigation app, which can direct the driver to the completely wrong side of a large block. (Addresses are not very granular in a city.) It’s interesting to me why Uber/Lyft allow this.
Amusing that they don't mention that they're able to better predict your location because of your phone's Wi-Fi. Tracking people is necessary [0] as Uber needs to provide better services . [0] https://www.npr.org/sections/alltechconsidered/2016/12/01/50...
1. https://news.ycombinator.com/item?id=15308771 Super-Accurate GPS Chips Coming to Smartphones in 2018 (ieee.org)
A big problem with Uber/Lyft is that drivers take all these fancy calculated positions and plug them into a standard navigation app, which can direct the driver to the completely wrong side of a large block. (Addresses are not very granular in a city.) It’s interesting to me why Uber/Lyft allow this.
There's also the fact that Google Map data is just flat out wrong in many places in the middle of the country, it says my house is my neighbor's house and so on down the block, everyone is off by one. I have tried to contact Google and get this fixed at least a dozen times over the past decade, always ignored. They used to have a whole community mapping thing where you could submit issues with the map, but those appa…