4 ms·

Interestingly, in image 2, the filtered data seems to be worse than the actual noisy data? Sure, the large spikes from sensor data were reduced, as seen with t

Interestingly, in image 2, the filtered data seems to be worse than the actual noisy data? Sure, the large spikes from sensor data were reduced, as seen with the blue line up in north which was considerably reduced, but seemingly at the cost of the more accurate tracks. We can see some "ground truth" - namely the map roads. I think if the source of the tracks are someone moving on a road (in a car etc.), it is safe to assume that the roads will be the most likely place to find them. In that image, it seems like we're seeing the tracks of some object moving on the road. EDIT: But nice work anyway, I work a lot with noisy GPS data for vessels, where there are no roads - only shipping routes / paths, and increased GPS jamming in some areas makes prediction models more useful.

n4r9 1y ago
Yeah, this sounds like a way to "smooth" the GPS trail to remove anomalies quickly, without paying attention to the road network. The problem of snapping a noisy GPS trail to the road network is known as map-matching. Good map-matching algorithms tend to use hidden Markov models, which are sort of like discrete Kalman filters. The state of the model is something like "which road segment is the truck on", and the predictive step employs routing algorithms to calculate transition probabilities between states. This is a dynamic algorithm that can be done on the fly - i.e. as each GPS point comes in - but I'd be very reluctant to do it in postgres.
- foota 1y ago
  So apps like Google maps do this? I'm always surprised when it jumps between roads. Like... You knew I've been on this road for the last ten minutes, you think I'm going to teleport into the tunnel beneath me?
  - n4r9 1y ago
    I'm not sure about Maps to be honest, but that sort of glitch is a strong indicator that they're just snapping to the nearest current road rather than doing proper routing calculations. My Toyota has a speed limit symbol on the dashboard which will occasionally show the speed of a slip-road going onto the motorway I'm already on. I'm guessing it's a similar phenomenon.
whilenot-dev 1y ago
I share the confusion. It depends on the measuring intent I guess, and it'd have been nice to say something about that and include some kind of indicator for these outliers. Here's the thing in Google Maps: https://www.google.com/maps/@47.1745904,7.2745602,14z/data=!5m1!1e1?entry=ttu&g_ep=EgoyMDI1MDkyNC4wIKXMDSoASAFQAw%3D%3D https://www.google.com/maps/@47.1745904,7.2745602,14z/data=!... From looking at the company website[0] I'd assume the goal could've been to get a better estimate about the total distance travelled during tracking analysis? Keeping that goal in mind, the error from the outliers was reduced significantly without causing too much disturbance on the accurate data. Nonetheless, including further measurements from speedo- and odometer in the sensor fusion at certain intervals would make this goal redundant and provide an even better estimate. [0]: https://traconiq.ch/ https://traconiq.ch/

n4r9 1y ago

Yeah, this sounds like a way to "smooth" the GPS trail to remove anomalies quickly, without paying attention to the road network. The problem of snapping a noisy GPS trail to the road network is known as map-matching. Good map-matching algorithms tend to use hidden Markov models, which are sort of like discrete Kalman filters. The state of the model is something like "which road segment is the truck on", and the predictive step employs routing algorithms to calculate transition probabilities between states. This is a dynamic algorithm that can be done on the fly - i.e. as each GPS point comes in - but I'd be very reluctant to do it in postgres.

foota 1y ago
So apps like Google maps do this? I'm always surprised when it jumps between roads. Like... You knew I've been on this road for the last ten minutes, you think I'm going to teleport into the tunnel beneath me?
- n4r9 1y ago
  I'm not sure about Maps to be honest, but that sort of glitch is a strong indicator that they're just snapping to the nearest current road rather than doing proper routing calculations. My Toyota has a speed limit symbol on the dashboard which will occasionally show the speed of a slip-road going onto the motorway I'm already on. I'm guessing it's a similar phenomenon.

whilenot-dev 1y ago

I share the confusion. It depends on the measuring intent I guess, and it'd have been nice to say something about that and include some kind of indicator for these outliers. Here's the thing in Google Maps: https://www.google.com/maps/@47.1745904,7.2745602,14z/data=!5m1!1e1?entry=ttu&g_ep=EgoyMDI1MDkyNC4wIKXMDSoASAFQAw%3D%3D https://www.google.com/maps/@47.1745904,7.2745602,14z/data=!... From looking at the company website[0] I'd assume the goal could've been to get a better estimate about the total distance travelled during tracking analysis? Keeping that goal in mind, the error from the outliers was reduced significantly without causing too much disturbance on the accurate data. Nonetheless, including further measurements from speedo- and odometer in the sensor fusion at certain intervals would make this goal redundant and provide an even better estimate. [0]: https://traconiq.ch/ https://traconiq.ch/