Im rewriting this in the Rust programming language: check the progress here:
My implementation of the map matching algorithm from this article (Althought with some modifications). The goal is to get the streets from a gps track.
This is how it looks like:
The gray line is the gps trace and the colored lines describe the map-matched most-likely route in the streets for the vehicle.
For reference read the resulting article.
You'll need python 3.5+ and a redis server running. The usage of a virtual environment is recommended.
Install from pypi:
$ pip install mapmatching
Or install from source:
$ cd mapmatching $ python setup.py install
Download data from OpenStreetMaps:
$ mapmatching download -h $ mapmatching download -96.99107360839844 19.441181182861328 -96.846435546875 19.59616470336914 -o streets.json
And load it to redis, by default it loads it to database 1 instead of redis default of 0.
$ mapmatching load -f streets.json
The two previous commands can be chained:
$ mapmatching download -96.99107360839844 19.441181182861328 -96.846435546875 19.59616470336914 | mapmatching load
Then run the match task with a geojson file with a single gps track. A sample
track that works with the sample bounding box is contained in the
directory of the repository.
$ mapmatching match -h $ mapmatching match data/route.geojson -o output.json
Optionally visualize it in the browser:
$ pip install geojsonio $ geojsonio output.json
if the output is too big you might need to copy+paste the contents of the output file into http://geojson.io
You can also import this as a module and use it in your python code. You'll still need a running redis instance.
import json from redis import Redis from mapmatching.match import match from mapmatching.lua import LuaManager from mapmatching.data import download_from_overpass, load_to_redis data = download_from_overpass(-96.99107360839844, 19.441181182861328, -96.846435546875, 19.59616470336914) redis = Redis(host='localhost', port='6379', db=0) load_to_redis(data, redis) with open('data/route.geojson', 'r') as routefile: route = json.load(routefile) coordinates = route['features']['geometry']['coordinates'] json_output = match( redis, LuaManager(redis), coordinates, 10, # How many points to process 50, # Radius in meters to use in the search for close points ) with open('output.json', 'w') as outputfile: json.dump(json_output, outputfile, indent=2)