As of 2020, Lyft is not a Corporate Member of the OSM Foundation.
Mapping Focus Areas
The Lyft OSM team does not participate in bulk editing or importing of data created by AI algorithms. Instead, the team is focused on improving the OSM map manually in ways that improve the rideshare experience. Lyft’s mapping team works with traffic roads (adding missing roads, lanes, destinations), relations (turn restrictions), barriers and access, walking paths and retail/commercial areas.
Lyft contributes edits to OSM in North America.
Lyft organized editing primarily concerns road network features and signage. Lyft collects valuable information such as missing roads, turn restrictions, one-way directions, destination signs, and other information that is wrong, missed or outdated in OSM. As sources in making edits, Lyft uses driver feedback, GPS traces, satellite and street-level imagery. The collected information is contributed to OSM with the help of our editing team. Edits are made to OSM according to Lyft-owned sources and are passed through internal quality control prior to being published. Lyft always follows the mapping guidelines mentioned in OSM wiki (where guidelines exist).
Here is the process followed by Lyft OSM team while editing:
1. Get generated area where GPS traces (internal data) differed from the existing road geometry or area where segments should be checked for missing or invalid data
2. Find the newest Lyft-owned street level imagery (internal data) and GPS traces to check the data
3. Use iD editor to fix issues according to the sources above
4. Audit compliance of edits to OSM's global and local policies by the Quality Control team
5. Upload changeset with appropriate comments
Lyft has a team of experts who audit edits made to OSM. Currently, our process is internal double-blind quality control. We use the tools listed in the wiki as well as manual analysis of OSM tags and geometries to ensure the quality of our work.
Lyft OSM team
Lyft has a team of trained OSM editors. The full list of the Lyft team is published on the GitHub page.
OSM Training Decks
Our training materials that we use to train OSM Lyft Team Members are publicly posted.
From 2018, when Lyft started to contribute to OSM, nearly 345k changesets have been published. More than 80% of edits related to the Lanes, Traffic roads, Destinations and Turn restrictions issues starting from missing lanes to complex remapping of intersections and ways.
|Types of edits||Changeset count|
|Barriers and Access||22,408|
|Airports and ports||2,821|
How to contact us
Lyft welcomes feedback and suggestions on improving the editing process. When members of the editing team receive feedback or comments on a changeset, it is considered a top priority to respond and make corrective action on their OSM edits if required. If you have any questions about the editing process, or a specific edit done by the Lyft team, please reach out by sending an email to dct-osm(at)lyft.com. Responses to inquiries received are typically sent within two business days. skudrashou_lyft and technician_lyft are acting as a primary contact person for the team.
- Huberty Mark & Corthell Clare (9 February 2021) ː "How Lyft discovered OpenStreetMap is the Freshest Map for Rideshare" Lyft
- Organized Editing Documentation: Lyft Data Curation https://github.com/OSM-DCT-Lyft/US
- Yuen, Albert (6 September 2019). “How Lyft Creates Hyper-Accurate Maps from Open-Source Maps and Real-Time Data”. Lyft .