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Who

What

Decision

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Proposal text  (ChatGPTgenerated)


1. Official OpenLR Documentation (by TomTom)

📄 OpenLR White Paper (Core Specification)

  • The foundational document that explains:

    • The encoding/decoding process

    • Location reference types

    • Binary and XML formats

    • Algorithms for location matching

📍 Link: https://www.openlr.org/docs/OpenLR-whitepaper.pdf

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2. OpenLR Reference Implementation (Java Library)

📦 Official GitHub Repository

  • TomTom’s open-source Java implementation of OpenLR

  • Includes:

    • Encoding/decoding tools

    • Sample map and test data

    • CLI tools

  • Great for understanding the logic and getting started with your own integration

📍 GitHub: https://github.com/TomTom/openlr

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3. OpenLR Encoder/Decoder Flow Diagrams

  • The whitepaper and GitHub repo include helpful flow diagrams and pseudo-code for:

    • Finding candidate locations

    • Generating location references

    • Decoding them onto different maps

This helps if you're implementing OpenLR in a language other than Java (e.g., C++, Python, JavaScript).

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4. Community/Examples

  • While OpenLR isn't widely discussed in public forums, you can find:

    • Example implementations or forks on GitHub (search "OpenLR").

    • Occasional integration notes in projects using OpenStreetMap or routing engines like GraphHopper or OSRM.

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❗Note: No "Plug-and-Play" Web API

  • OpenLR is a specification and library, not a hosted API or web service.

  • You typically:

    • Integrate the encoder on your side (to generate references).

    • Transmit the encoded data (binary or base64).

    • Use the decoder on the recipient side to map-match to their own map data.

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Bonus: Alternatives and Extensions

If your use case goes beyond what the core OpenLR offers, you might consider:

  • OpenLR+ (an extended version used internally by some companies)

  • Custom adaptations for area locations, GeoCoordinate encoding, etc.


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