there is also smart road sense https://smartroadsense.it/apps/
Regarding ‘mapping potholes’, I expect this to be a layer applied to OSM, not data contained within OSM. It will be open source information, for people that can use it.
Thanks,
Chris
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Are there any areas where it has been used extensively? Any write-ups of how effective it was? It sounds like a good subject for an OSM diary entry.
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Anyone know if SmartRoadSense is still maintained? I can’t find a contact email address.
Cheers,
Chris
I was a co-founder of a start-up that does something similar as Roadroid. Basically we can get accelerometer data from a smartphone to convert to IRI (~road quality index), so road managers can plan maintenance accordingly.
I don’t work there anymore and I don’t know the current state-of-the-art on this matter, but what I do know from experience is that these values are not perfect, but it does work nicely providing an overall of road quality (excellent, good, bad, extremely bad). Some road agencies were (2 years ago) using this kind of technology, on a pilot basis. I am not aware on any road agency using this as a replacement of traditional surveys, nor letting their contractors do that.
On the OSM side, while this excellent/good/bad/extremely bad information can be directly related to the smoothness=* tag, I am not sure if this info can be maintained on a regular basis. For example, on these apps they usually divide surveys into segments (like 20 m/100 m/1 km segments), so one has to group or split (unlikely) that to fit the OSM road segments. Probably it can be done programmatically, trying to create something that matches OSM data, and feed it constantly.
Not sure what you guys think about it, but this is something that cannot be easily done on my point-of-view.
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Dohh, missed that.
Matheus,
Is the app you worked on open source, need to check Roadroid? If so, it should be possible to compare the features with SmartRoadSense, and see what the next step is.
Thanks,
Chris
I’ve emailed SmartRoadSense.
Chris
Andy, not familiar with ‘OSM diary entry’, could you say a little more?
Chris
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For example, on these apps their usually divide the surveys into segments (like 20 m/100 m/1 km segments),
ideally they would align to OpenStreetMap way divisions so that we don’t have to split 
but it still would be a burden for mappers mapping “manually” because they would not know how to deal with it on way splits
Hi, all.
I wrote up a page here, to try to get this in some sort of order. I welcome any constructive additions.
Many thanks,
Chris.
No, Chris, the app I was working on is not open source and given I don’t work there anymore, I can’t do much about that, unfortunately. Regarding features, it was very similar to Roadroid at that time.
Yes, this could be done on the app side, using existing OSM road segments as the “survey segments”. Probably this isn’t super hard to implement, but I’m not sure how open the devs are.
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My email to SmartRoadSense was bounced, so I assume the email address has been retired. I have written to the two main developers, that I found on the GitHub page.
Chris
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Roadroid had an app since 2011, so we are probably the longest lasting app for the issue. Whats been seen is the appeance of image detection for road damages. Pottholes is the typical common road user preception of road condition, while road engineers talk about IRI and Cracking, Raveling, Rutting etc.
It depends on the type of decisions to make for the input, on paved roads ther could be (temporary) pothole fixing but also pavement planning. Smartphone apps for roadcondition havent been successfull in crowd sourcing, it needs to many users to be fruitful and and the input from car systems will be impossible to compete with for smartphone app solutions. At least in countries where the built i car solutions will be allowd, probably large parts of the west world.
We still see a market for apps like Roadroid, where road engeineers wants to map a road network quickly in a campain, or on low volume roads/unpaved where not to much crowd traffic can be expected. The use of image detection will definately be a part of the future, but the accelerometer input still important,
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That is great, and also welcome and thanks for posting here!
In OSM we map the overall condition of the surface, and specifically which kind of vehicles (or wheeled contraptions) can use it, as smoothness. This includes potholes, which are probably one of the most common factors that distinguishes poor from good roads, especially for tarmac (see examples), but it’s definitely not limited to potholes. Is this the sort of thing that Roadroid measures?
Any one who enters data into OSM has to agree to make the data available to the public under a highly permissive license, even for non-commercial purposes, so I don’t think the big companies that are collecting data with car systems will allow us to use it. Do you see a market for crowd sourcing in this area? I would love an app that links the accelerometer data to the roads in the OSM database, translates it into OSM smoothness values, probably after a period of calibration, and allows me to upload it to the database after I’ve reviewed it. Some questions would need to be addressed, such as how to average the observations of multiple users for the same road, or the issues that others here have pointed out (e.g. how to deal with a single, easily avoided pothole on an otherwise excellent surface). But overall I think the community might be interested in this sort of thing!
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Hi, Lars. I will read your post shortly, but just wanted to say that it’s great to see you here.
Chris
UK
For info, it sounds like development of SmartRoadSense may be getting reinvigorated. I’ve reached out to the developers.
Chris
StreetComplete comments responding that blog has some extra insights too for interested parties: new Quest: surface smoothness · Issue #1630 · streetcomplete/StreetComplete · GitHub