Fabio/brouter
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 1

Clarify some wordings & format table

Browse source
This commit is contained in:
Manuel Fuhr 2023-10-18 21:24:48 +02:00
parent 94b3727840
commit eb43a6cf2a
1 changed files with 58 additions and 47 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

105
docs/developers/environmental_considerations_and_pseudo_tags.md
View file

@ -1,6 +1,12 @@
Environmental considerations (penalties for traffic, noise, town, no river, no forest) are possible due to the creation of pseudo tags during processing OSM data by spatial SQL queries in https://github.com/abrensch/brouter/blob/master/misc/scripts/mapcreation/brouter.sql. During this processing, roads are extended by a 32 m buffer creating 64 m wide lines. Then it is calculated what percentage of such line is at a specific distance to a noise source or within a forest, for example. The percentage is converted to a factor and the factor is assigned to a class. Ways that pass through different environments and are represented by a single OSM way can be problematic because the class is always based on the average environment along an entire OSM way. For traffic, calculations are on another level of complexity.
---
parent: Developers
---
### consider_noise, noise_penalty
# Environmental considerations
Environmental considerations (penalties for traffic, noise, town, no river, no forest) are possible due to the creation of pseudo tags during processing OSM data by spatial SQL queries in [brouter.sql](https://github.com/abrensch/brouter/blob/master/misc/scripts/mapcreation/brouter.sql). During this processing, roads are extended by a 32 m buffer creating 64 m wide lines. Then it is calculated what percentage of such line is at a specific distance to a noise source or within a forest, for example. The percentage is converted to a factor and the factor is assigned to a class. Ways that pass through different environments and are represented by a single OSM way can be problematic because the class is always based on the average environment along an entire OSM way. For traffic, calculations are on another level of complexity.
### noise_class
For proximity of noisy roads (secondary and higher). The noise factor represents the proportion of a road's buffer area that lies within the 64-meter buffer of noisy roads. This proportion is reduced:
@ -9,27 +15,32 @@ For proximity of noisy roads (secondary and higher). The noise factor represents
- 3 times if maxspeed is 75 - 105 for primary and secondary
- other secondary roads 5 times
Noise class is roughly proportional to the noise factor:
`noise_class` is roughly proportional to the noise factor:
noise_factor = noise class
| `noise_factor` | `noise_class` |
| -------------- | ------------- |
| < 0.1 | 1 |
| < 0.25 | 2 |
| < 0.4 | 3 |
| < 0.55 | 4 |
| < 0.8 | 5 |
| ELSE | 6 |
- < 0.1 = '1'
- < 0.25 = '2'
- < 0.4 = '3'
- < 0.55 = '4'
- < 0.8 = '5'
- ELSE = '6'
To be classified as noise class 6, a way must be less than 13 m on average from the middle of the carriageway of a motorway with a maximum speed exceeding 105. For a class 5, the distance must be up to 35 meters. (1 - noise_factor) \* 64 m for a given class determines the distance
To be classified as noise class 6, a way must be less than 13 m on average from the middle of the carriageway of a motorway with a maximum speed exceeding 105. For a class 5, the distance must be up to 35 meters. (1 - noise factor) \* 64 m for a given class determines the distance
| highway | maxspeed | max `noise_class` |
| -------------- | -------- | ----------------- |
| motorway,trunk | > 105 | 6 |
| motorway,trunk | 105 | 5 |
| motorway,trunk | 75 | 5 |
| primary | > 105 | 4 |
| primary | 105 | 4 |
| primary | 75 | 3 |
| secondary | > 105 | 3 |
| secondary | 105 | 3 |
| secondary | 75 | 2 |
**Max noise class:**
| Max speed | Motorway, trunk |Primary|Secondary |
|--- |:---: |:---: |:---: |
| >105 |6 |4 | 3 |
| 105 |5 |4 |3 |
| 75 |5 |3 |2 |
### consider_river, no_river_penalty
### river_class
OSM data recognized as river:
@ -38,16 +49,16 @@ OSM data recognized as river:
Waterways have 32 m wide buffers. Water areas have 77 m wide buffers.
river_see = river class
| `river_see` | `river_class` |
| ----------- | ------------- |
| < 0.1 | 1 |
| < 0.3 | 2 |
| < 0.5 | 3 |
| < 0.8 | 4 |
| < 0.9 | 5 |
| ELSE | 6 |
- < 0.17 = '1'
- < 0.35 = '2'
- < 0.57 = '3'
- < 0.80 = '4'
- < 0.95 = '5'
- ELSE = '6'
### consider_forest, no_forest_penalty
### forest_class
OSM data recognized as forest:
@ -58,30 +69,30 @@ No forest buffers are used.
Imagine you trace the way with a pencil drawing lines 62 meters wide. Then estimated_forest_class=6 corresponds to the case that at least 98% of the line is in the woodland. This number is called a green factor.
green_factor = forest class
| `green_factor` | `forest_class` |
| -------------- | -------------- |
| < 0.1 | NULL |
| < 0.2 | 1 |
| < 0.4 | 2 |
| < 0.6 | 3 |
| < 0.8 | 4 |
| < 0.98 | 5 |
| ELSE | 6 |
- < 0.1 = NULL
- < 0.2 = '1'
- < 0.4 = '2'
- < 0.6 = '3'
- < 0.8 = '4'
- < 0.98 = '5'
- ELSE = '6'
### consider_town, town_penalty
### town_class
Town_class is determined by population data from OSM.
Class
| population | `town_class` |
| ------------------ | ------------ |
| < 80 k people | 1 |
| < 150 k people | 2 |
| < 400 k people | 3 |
| < 1 million people | 4 |
| < 2 million people | 5 |
| > 2 million people | 6 |
- 1 = 50-80 k people
- 2 = 80-150 k people
- 3 = 150 - 400 k people
- 4 = 400 - 1,000 k people
- 5 = 1 - 2 million people
- 6 = > 2 million people
### consider_traffic, traffic_penalty
### traffic_class
(modified copy from the sql file).
OSM data used to estimate the traffic: