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 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
data/ 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