I’m working on a side project with a number of cycling charities around mapping cycle lane quality/material.
The idea being to create a global standard for measuring cycle lane quality for comparison / research.
It’s all a bit experimental right now, and has predominantly focused on using phone sensors to capture measurements (g-forces) to date.
In short we have now come to the conclusion, due to the amount of variables to be accounted for, this is not a scaleable solution.
You can read more about why here:
UPDATE: I can’t post links, Google “Trek View blog”
Seeing as the bikes will have a 360 camera (and potentially ground facing GoPro’), I’m now trying to take advantage of using these images to identify path quality / material type using computer vision.
I know this technology exists in roadway maintenance and there are a lot of available models for tarmac/concrete roads (and an equal number of commercial products).
I’m reaching out to the community to see if anyone has any experience / tips / good links to research using computer vision to measure quality of less uniform pathways (gravel, mud, etc.)?
I’ll keep this thread updated with progress. As with all our work, I will open-source anything we build.