Mappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of "Matchers" that enable matching a GPS trace (series of GPS coordinates) to a map.

The current matchers are:

• LCSSMatcher: A matcher that implements the LCSS algorithm described in this paper. Works best with high resolution GPS traces.
• OsrmMatcher: A light matcher that pings an OSRM server to request map matching results. See the official documentation for more info.
• ValhallaMatcher: A matcher to ping a Valhalla server for map matching results.

Currently supported map formats are:

• Open Street Maps

pip install mappymatch

If you have trouble with that, check out the docs for more detailed install instructions.

The current primary workflow is to use osmnx to download a road network and match it using the LCSSMatcher.

The LCSSMatcher implements the map matching algorithm described in this paper:

Zhu, Lei, Jacob R. Holden, and Jeffrey D. Gonder. "Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data." Transportation Research Record: Journal of the Transportation Research Board 2645 (2017): 67-75.

usage:

from mappymatch import package_root from mappymatch.constructs.geofence import Geofence from mappymatch.constructs.trace import Trace from mappymatch.maps.nx.nx_map import NxMap from mappymatch.matchers.lcss.lcss import LCSSMatcher trace = Trace.from_csv(package_root() / "resources/traces/sample_trace_1.csv") # generate a geofence polygon that surrounds the trace; units are in meters; # this is used to query OSM for a small map that we can match to geofence = Geofence.from_trace(trace, padding=1e3) # uses osmnx to pull a networkx map from the OSM database nx_map = NxMap.from_geofence(geofence) matcher = LCSSMatcher(nx_map) matches = matcher.match_trace(trace) # convert the matches to a dataframe df = matches.matches_to_dataframe()

Check out the LCSS Example for a more detailed example of working with the LCSSMatcher.