Measure traffic speeds. Demand safer streets.

Open-source speed monitoring for neighbourhood streets.

Collect the evidence yourself. velocity.report turns a Raspberry Pi and a radar sensor into a local speed monitor. Download the Pi image, aim it at your street, and generate a PDF you can take to City Hall: no cameras, no licence plates, no cloud accounts.

Before and after: Measure before. Measure after. Then you can see whether the changes worked, which is better than arguing from memory.

Privacy by design: No cameras, no faces, no licence plates. Measure traffic, not identity.

Open source: Read the code, run it on your own Pi, and keep the data on hardware you control.

Sample Report →

GEN 01 · RADAR

IN THE WILD

Ready now. Measuring streets today.

Radar speed monitoring on Raspberry Pi. It already produces PDF reports, percentile breakdowns, and hourly patterns for real residential streets.

STATUS STABLE RELEASE v0.5.0 HARDWARE OmniPreSense RADAR

GEN 02 · LIDAR

RESEARCH PREVIEW

Real streets, open questions.

LiDAR records where road users move without taking their picture. The pipeline, maths, and 25 published street scenes are open for inspection. It is research equipment, not an appliance, yet.

STATUS EXPERIMENTAL PIPELINE CALIBRATING HARDWARE Hesai LiDAR

How it works

Three pieces. One PDF.

01 · RECORD

Point it at the street.

Mount it on a window or fence and the radar measures passing vehicle speeds. No images. No identifying data.

02 · STORE

A Raspberry Pi keeps the data.

Everything runs locally on a Pi. The SQLite database stays on the device. Re-aim it, let it run for days or weeks, and keep the data on hardware you control.

03 · REPORT

Generate the PDF people can use.

One click generates a council-ready PDF with speed distributions, percentiles, hourly patterns, and site information. It leaves less room for hand-waving and more room for the actual problem.

Downloads

Pick your platform.

Raspberry Pi image

Release notes →

Raspberry Pi image

v0.5.1-pre25

sha256:af4391cef624cc7f3668f010bd09f14fd8e8b449e2610ec6ec46327271fe3785

Raspberry Pi Imager custom repo

Install Raspberry Pi Imager, then run this in a terminal. The --repo flag should work everywhere. Only the path to the binary changes.

cd "/Applications/Raspberry Pi Imager.app/Contents/MacOS/" && ./rpi-imager --disable-telemetry --repo https://velocity.report/rpi.json

Server downloads

Release notes →

Server · Linux ARM64

v0.5.0

sha256:1e96dc4ef660f35dcbde98d3b98a7f645e3419d95f3036b029080621321faf5e

Server · macOS ARM64

v0.5.0

sha256:b263e8a108c58e71f608cb2727fde2b2fd5c3f40e38353b9ef8c2d59d1b094d4

Research

LiDAR research: watch a street become evidence.

RESEARCH PREVIEW OPEN PIPELINE

LiDAR measures where road users move through a street without taking camera images. The code is real, the maths are published, and the results are still being calibrated.

The radar setup gives you speed data and a PDF. LiDAR adds position, direction, and the space between road users. It does not yet give you a finished set of street-safety metrics to accept on sight. That is why the recordings and the unanswered questions are public.

One part of that future is the Traffic Description Language: a way to ask plain-English questions of the fused transit data. Questions like how closely drivers pass work crews, how much space cars leave cyclists in a bike lane, or how many cars come to a complete stop at an intersection when school gets out. In other words, the questions people actually ask once the speed chart has done its job.

TDL design Pipeline maths Scene publishing plan

25 recordings. No camera images hiding in the small print.

VelocityVisualiser.app · macOS Explore street scenes → LiDAR architecture ↗

Get the evidence, or help build the next part

For residents & advocates

Measure your street.

You do not need to be a developer. Flash the Pi image, aim it out of a window, leave it running for a week, and take numbers to the next meeting instead of a story that someone can wave away.

Flash the Raspberry Pi image once; after setup, the main workflow lives in the web dashboard
Council-ready PDF with speed distributions, hourly patterns, and percentiles
Privacy by design: radar only, no faces, no plates, and no cloud account
Discord help for mounting, aiming, setup snags, and making the case

Download the Pi image Setup guide →

For engineers & researchers

Help us see the street.

The radar pipeline is the most mature part of the project. The LiDAR pipeline is open and still calibrating. Geometry, tracking, and classification still have real unanswered questions, which is another way of saying there is useful work to do.

Open-source pipeline, published maths, and a public list of open questions
LiDAR research preview: point clouds, tracking, classification
Discord for fast design triage; GitHub issues and PRs for decisions that need a paper trail
Apache-2.0 licensed, documented, and backed by calibration data

Repository Open questions → Discord guide →

FAQ

Common questions

Quick answers to the questions people usually ask before they download.

What is this?

An open-source traffic speed monitor. Plug a radar sensor into a Raspberry Pi, let it measure how fast vehicles pass, and it produces a PDF with speed distributions, hourly patterns, and percentile breakdowns. No cloud, no cameras, and no habit of collecting things it does not need.

Who is this for?

People trying to show that traffic on their street is a safety problem, and to do it with numbers rather than a weary look at the road. Residents, parent groups, neighbourhood campaigns, and anyone who has been told to come back with evidence.

What does it measure?

Vehicle speeds. A radar sensor records how fast vehicles pass and stores the results on a Raspberry Pi. No faces, no licence plates, and no images of any kind.

Where does the data go?

Nowhere special. It stays on your device in a local database. There is no cloud account, no silent upload, and no side business in learning things about your street. Data leaves only when you decide to share the finished PDF.

What about LiDAR?

LiDAR is still research-stage. The pipeline, maths, and public street scenes are open, and the current release includes a macOS visualiser for engineers and curious users. Today, the dependable PDF path is radar. LiDAR still expects an engineer in the room.

How do I get started?

Follow the setup guide. You need a Raspberry Pi and an OmniPreSense radar sensor. By the end, you should have a working speed monitor and a PDF report fit for a council meeting.