Open Stapawe opened 1 year ago
Maybe create a new file pseudo_tags.md
inside of https://github.com/abrensch/brouter/tree/master/docs/developers/?
Hello Stapawe,
Sorry, I have not the time to create a documentation explaining EXACTLY what is calculated!
If you need that, yes the answer is the brouter.sql!
As a first help to developpe a new profile (or update an existing profile) I added explanations in my profile that can also be used as example for a pseudo-tags usage:
(It describes the different use cases and the tag values when they are not implicit) See: assign consider_noise = false # %consider_noise% | set to true to favor a low-noise route | boolean -# usage: try to find a route without noise -# the pseudo-tag "estimated_noise_class" can be now used for this (noise coming from motorway, primary, sencondary, tertiary and internatinal airports)
assign consider_river = false # %consider_river% | set to true to favor a route along rivers or sees | boolean -# usage: try to find a route along "water" -# the pseudo-tag "estimated_river_class" can be now used for this (considered are the "water" surfaces -exception wastewater!- and the river,canal)
assign consider_forest = false # %consider_forest% | set to true to favor a route in forest or parks | boolean -# usage: try to find a route within a forest (or green area) -# the pseudo-tag "estimated_forest_class" can be now used for this (considered are 'forest','allotments','flowerbed','orchard','vineyard','recreation_ground','village_green', 'garden','park', 'nature_reserve')
assign consider_town = false # %consider_town% | set to true to bypass cities / big towns as far as possible | boolean -# usage: try to find a route which bypass big towns and cities -# the pseudo-tag "estimated_town_class" can be now used for this (considered are towns/cities with a population > 50.000) -# population class -# < 50.000 no tag -# < 80.000 1 -# < 150.000 2 -# < 400.000 3 -# < 1.000.000 4 -# < 2.000.000 5 -# > 2.000.000 6 -# ways having a river or forest tag are not tagged, this enabling to cross a big town allong a river or through parks/forest
assign consider_traffic = 1 # %consider_traffic% | how do you plan to drive the tour? | [1=as cyclist alone in the week, 0.5=as cyclist alone at weekend, 0.3 =with a group of cyclists, 0.1=with a group of cyclists at week-end] -# usage: try to find a route with few cars/trucks traffic -# the pseudo-tag "estimated_traffic_class" was redesigned and can be used for this. Considered are: -# population of towns (+ distance to the towns) -# industrial& retail areas -# airports international -# motorway density -# highway density (xceptions near junctions between motorways and primary/secondary/tertiary) -# mountain-ranges
If you have an other documentation available, please contact affischerdev (I have no idea, where to store it) Regards
Hello EssBee59 I've made PR https://github.com/abrensch/brouter/pull/612 and this information is included. Sorry, that I didn't write it here earlier. Regards
Thank for your work!
I will take a look as soon I get time for that. If it helps, here a short ppt I prepared some weeks ago... but I did not found the right place to save it. Regards myInfoEn_Std.pdf
It would be good to insert updated diagrams (so not 33 m buffers)
@Stapawe, the PDF is actually correct: https://github.com/abrensch/brouter/blob/76265e7713ad203ee6679a810121d2bd22f78074/misc/scripts/mapcreation/brouter.sql#L47 What needs to be updated are the comments and the variable names in the brouter.sql: https://github.com/abrensch/brouter/blob/76265e7713ad203ee6679a810121d2bd22f78074/misc/scripts/mapcreation/brouter.sql#L44-L45 because they're misleading.
I mean traffic, noise, no river, no forest and town penalties. Because I couldn't find documentation explaining what exactly is calculated, I tried to analyse brouter/misc/scripts/mapcreation/brouter.sql and I made some notes (about 400 words). I can paste them, but I'm not sure where https://github.com/abrensch/brouter/blob/master/docs/developers/profile_developers_guide.md ? wiki? I think in profiles would be too many places.