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Calculating Level of Traffic Stress using Open Street Map data

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LTS-OSM - Calculating Level of Traffic Stress using Open Street Map Data

This code calculates cycling Level of Traffic Stress for all road and path segments in a region using data from Open Street Map.

Background

This code is adapted from Bike Ottawa's LTS code, modified to include Level of Traffic Stress for intersections.

Usage

  1. Generate an OSM query file for the region you want to study.
    • Go to openstreetmap.org, search for the region you want to download (i.e. "Victoria"), then find the matching region in the list on the left side.
    • Click on the region you want, which should open a page for a relation that says something like "Relation: Victoria (2221062)" at the top. - Scroll down in the list of tags until you find wikidata, i.e. wikidata:Q2132 for Victoria, Canada.
    • In a terminal, run build_query.py with this key-value pair: run python build_query.py victoria wikidata Q2132 to generate a file victoria.query.
  2. Download OSM data to get a list of tags. In a terminal, run wget -nv -O victoria.osm --post-file=victoria.query "http://overpass-api.de/api/interpreter", changing the input and output filenames as needed.
  3. Change the city name in the script LTS_OSM.py. Run LTS_OSM.py to download the network for the region and calculate LTS. This outputs a dataframe called all_lts.csv which contains all the ways, their assigned LTS, and the decision criteria that led to that LTS. In particular, the columns lanes and maxspeed may contain NaN if this information is not present in the OSM tags and the data can be filtered to exclude these.
  4. Plot resulting LTS map with LTS_plot.py.
  5. Plot an isochrone map for different LTS thresholds with isochrone.py. This requires both the saved graph object and the dataframe with LTS levels calculated.

Coming Soon

This code is under active development. Check out the Issues for a list of improvements that will be made soon.

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