Open Source Routing Machine (OSRM)
About this project
Open Source Routing Machine
High performance routing engine written in C++ designed to run on OpenStreetMap data.
The following services are available via HTTP API, C++ library interface and NodeJs wrapper:
- Nearest - Snaps coordinates to the street network and returns the nearest matches
- Route - Finds the fastest route between coordinates
- Table - Computes the duration or distances of the fastest route between all pairs of supplied coordinates
- Match - Snaps noisy GPS traces to the road network in the most plausible way
- Trip - Solves the Traveling Salesman Problem using a greedy heuristic
- Tile - Generates Mapbox Vector Tiles with internal routing metadata
To quickly try OSRM use our demo server which comes with both the backend and a frontend on top.
For a quick introduction about how the road network is represented in OpenStreetMap and how to map specific road network features have a look at the OSM wiki on routing or this guide about mapping for navigation.
Related Project-OSRM repositories:
- osrm-frontend - User-facing frontend with map. The demo server runs this on top of the backend
- osrm-text-instructions - Text instructions from OSRM route response
- osrm-backend-docker - Ready to use Docker images
Documentation
Full documentation
Contact
- Discord: join
- IRC:
irc.oftc.net
, channel:#osrm
(Webchat) - Mailinglist:
https://lists.openstreetmap.org/listinfo/osrm-talk
Quick Start
The easiest and quickest way to setup your own routing engine is to use Docker images we provide.
There are two pre-processing pipelines available:
- Contraction Hierarchies (CH)
- Multi-Level Dijkstra (MLD)
We recommend using MLD by default except for special use cases such as very large distance matrices where CH is still a better fit for the time being.
In the following we explain the MLD pipeline.
If you want to use the CH pipeline instead replace osrm-partition
and osrm-customize
with a single osrm-contract
and change the algorithm option for osrm-routed
to --algorithm ch
.
Using Docker
We base our Docker images ([ba