OpenBikeSensor
Passing distance measurement for cyclists
Open Innovation, Open Source, Open Data, Open Science
Forum
Matrix
Github
Documentation
SupportAsk and discuss
Come over to our Discourse forum for discussions with other interested and active community members on topics like: help and support, local groups, projects, events and further developments.
Build & measure
Build your own device. We will support you as much as we can. How about joining a local group of builders and cyclists, and join a collective order to save on parts?
Develop
We publish everything we create as open source. Everything is available on GitHub, including the software code, schematics, blueprints, CAD models, instructions and documentation.
The OpenBikeSensor is a small electronic device attached to a bicycle that records the distance to passing vehicles during the ride.
It’s not a finished product, and you cannot purchase an OpenBikeSensor. But there is plans and information available publicly to build your own. Have a look at Github, where there are repositories for the firmware, PCBs, the files for 3D printing the case, the software for the frontend and backend of the data portal, and this documentation page. You’re invited to join and help develop the sensor.
In our data portal, users can upload data recorded with their OpenBikeSensors and optionally share them as Open Data with the public.
Visualisation
An important part of this project is enabling the analysis of the collected data. That’s why we write software to extract interesting values from the recorded track files and visualise them.
Here we show an example visualisation of a number of overtaking manoeuvres and their distances from Stuttgart, Germany. The values come from an experienced cyclist who moves in traffic routinely with confidently. Of course this cyclist was passed many times below the legal threshold of 1.5m, some measurements are even as low as 50cm.
Another example shows a single overtaking, of which a video recording was available as well. We overlay GPS information as well as the recorded sideways distance to the passing vehicle. We hope presenting information in context like this makes it easier to relate and get a feel for the danger the cyclist is exposed to in this very moment.
If you have ideas for visualisation, automation, software and tool development and analysis of the data available from the recorded tracks, or you’re just interested in joining the project or keeping up to date with it, please join the community.