[tgbugs]

I wonder if there are existing data sources that could be used to implement an optimal pot hole patching priority lists at scale.

Identify pot hole locations. Combine with traffic metrics for those locations. Then use a combination of some pot hole nuisance metric (size, depth, location in lane, number of cars that could hit it per unit time based on traffic metrics), a cost to repair for a given repair type metric (should include traffic disruption cost estimates), then have an estimate for future degradation if it is not repaired and the cost of that applied at a few time points .... I'm sure there are plenty of implementations of various versions of the algorithm, but I wonder whether there are open data sources ....

A quick search suggests that most approaches are municipality based crowd sourcing efforts. A stream from the radars from various vehicles could provide something that was up-to-date enough to avoid false positives that had already been fixed .... Things like streetview and various aerial photography datasets probably update too slowly ... though I know of some potholes that have existed through multiple recaptures.

0. https://par.nsf.gov/servlets/purl/10636488 1. https://doi.org/10.1016/j.jag.2023.103335

I guess the days of citizens grabbing their shovels and going to fix the roads are becoming a thing of the past. Which is a shame because the total cost of asphalt needed to fix most potholes is less than the cost of a single tire repair.