Organised Editing/Activities/OptimoRoute

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Introduction

OptimoRoute is conducting an organized editing activity to improve truck road access data on OpenStreetMap. Our primary focus is on improving the accuracy of truck (heavy goods vehicle) road access information, including both restrictions and designated routes, across various regions worldwide. This project is being carried out by a dedicated team following detailed procedures to ensure high-quality and precise contributions.

The main goal of this activity is to update truck road access data, particularly in areas where current information may be incomplete or outdated. For more information about OptimoRoute and our services, visit our website.

Project objectives

  • Improve the accuracy and detail of truck road access data in targeted areas.
  • Working with tags such as maxheight, maxweight, hgv, and other related tags.
  • Use government-issued documents and maps—whether national, regional, or local—combined with publicly available information in OSM tools, to identify areas of interest.
  • Identify and verify missing or incorrect data in OSM using imagery integrated into iD Editor, primarily Bing Streetside and Mapillary.
  • Contribute to OSM following the Organised Editing Guidelines.

Team members

Editing techniques

We will use iD Editor and JOSM to make edits to the map. The tasks will include updating road and path tags. Team members will make manual edits, focusing on ensuring the highest level of accuracy in road and path data. For internal quality reviews, we will use OSMCha and Osm-revert.

Data sources

To identify targeted areas for this project, publicly available government-issued documents or maps—whether national, regional, or local—will be consulted. The OSM Truck QA Map tool will be used to identify missing maxheight tags. Additionally, the Mapillary traffic signs search tool will assist in locating relevant traffic signs. Overpass turbo queries will be utilized to check the current status of OSM tags.

The identification of missing tags or inconsistencies in OSM, as well as data edits will be verified using imagery integrated in iD Editor, primarily Bing Streetside and Mapillary.

In cases of missing imagery or signs, OSM tags may be added based solely on local laws where those laws clearly define truck access, do not require erected signs for the rule to be in effect, and may legally be used as a source for OSM mapping. This approach applies in countries where official laws and similar legal texts are not subject to copyright, or where their reuse is otherwise legally permitted. The United States is a prominent example. In the United States, government laws, excluding building codes or technical standards developed by private organizations, are not subject to copyright and are considered public domain. For more information about the United States, see Edict of government and Copyright law of the United States.

Changeset policy

All changesets will include the hashtag #OptimoRoute to ensure transparency and track project contributions. Changesets will be uploaded after editing a smaller area, typically a cluster of streets, to keep the changesets manageable and minimize the risk of conflicts with ongoing community edits. Sources referenced in the changesets will be linked for transparency. We will follow OSM’s rules for organized edits and ensure changes are internally reviewed for quality.

Timeline

The editing activity will take place from early November 2024.

Contact

For questions or feedback, please contact the project lead at osm@optimoroute.com

Community Consultation

We contacted the community using the following communication channels:

Results

United States

From November 2024 through September 2026, we made almost 43,000 changesets on approximately 812,000 ways.

The edits consisted of four main types:

  1. Truck access restrictions and designations, predominantly using hgv tags, in urban areas where the main city has a population over 100,000
  2. Tagging low underpasses, predominantly using maxheight tags, in the same urban areas
  3. Truck designated statewide routes, including the National Truck Network, predominantly using hgv=designated tags
  4. Weak bridges statewide, predominantly using maxweight tags, where a usable source for identifying them was available

Our main rough success metric has been the density of truck restricted and locally designated ways per city, calculated as the number of restricted and designated ways divided by the land area of each city in square miles. Based on that metric, we observed the following improvements across 340 targeted cities with populations over 100,000:

  • The number of targeted cities with satisfactory truck coverage, defined as a target density of 1.5 or higher, increased from 59 to 222 cities, or from 17% to 65% of targeted cities.
  • Across all 340 targeted cities, the overall average density increased almost fivefold, from 1.7 to 8.3.

On top of the above, there were numerous cities with populations below 100,000 that are within the targeted metro areas and were improved along the way. We reviewed a sample of results for 240 such cities, and 66% now have satisfactory truck coverage, with an overall average density of 15.3.

For the statewide metrics, we visually evaluated the coverage of known truck designated routes and the National Truck Network after our team completed the work. Across the 50 states, the number of states with satisfactory truck route coverage increased from 9 to 32, or from 18% to 64%.


United Kingdom

From May 2025 through November 2025, we made around 3,000 changesets on approximately 13,500 ways.

The edits predominantly used maxweightrating:hgv and maxweightrating:hgv:conditional tags, and were focused largely on urban areas with populations over 100,000.

Our main rough success metric has been the density of truck restricted ways per city, calculated as the number of truck restricted ways divided by the land area of each city in square miles. Based on that metric, we observed the following improvements:

  • The number of targeted cities with satisfactory truck coverage, defined as a target density of 1.5 or higher, increased from 25 to 42 cities, or from 42% to 71% of targeted cities.
  • Across all covered city areas, the overall density doubled, increasing from 1.4 to 3.0.


Australia

From December 2024 through May 2026, we made around 2,000 changesets on approximately 10,000 ways.

The edits predominantly used maxweight tags and were focused on urban areas with populations over 100,000.

Our main rough success metric has been the density of truck restricted ways per city, calculated as the number of truck restricted ways divided by the land area of each city in square miles. Based on that metric, we observed the following improvements:

  • Using a target density of 0.5 or higher as satisfactory truck coverage, we significantly improved coverage in Sydney, Melbourne, Adelaide and Gold Coast. A more modest improvement was made in Brisbane, while Canberra and Greater Geelong already had good coverage. The lower target compared with 1.5 in other countries where we performed the same task reflects the typically much larger land areas of Australian cities.
  • Across all covered city areas, the overall density increased from 0.17 to 0.32.
  • Among the 10 largest cities, the overall density more than doubled, increasing from 0.21 to 0.48.
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