Bicycle zones are working — here’s what the data shows

Bicycle zones have become a familiar sight in Belgium. The idea is simple: cyclists get priority across the full width of the road, and cars are guests that must not overtake them. But putting up a sign is not the same as changing behaviour. Is the bicycle zone actually working? The honest answer: you only know once you measure.

Why gut feeling is not enough

There is no shortage of opinions about bicycle zones. Residents mostly notice the car that squeezes past, cyclists remember that one dangerous overtake, and drivers experience the street as a detour. All of these impressions are real, but together they do not add up to a reliable picture. A one-off count on a sunny Tuesday says little about a rainy Saturday or the school run.

For a mobility team that is a problem. A bicycle zone costs money, takes political courage and sometimes meets resistance. Anyone who wants to adjust course or design the next street needs arguments that go beyond intuition.

What cameras measure

With cameras and AI, you measure a bicycle zone day and night, without sensors in the road surface and without someone at the kerb with a tally sheet. The key indicators are:

• Cycling volume. How many cyclists use the street, per hour and per day, and how does that change after the redesign?
• Traffic mix. What share of traffic is made up of cyclists, cars, pedestrians and other road users?
• Overtaking. How often do cars overtake cyclists, even though that is forbidden in a bicycle zone?
• Peak moments. When is it busy, and when do conflicts arise?

What the data reveals

Put these indicators side by side and the conversation changes. Instead of “it feels unsafe”, you point to the hours and places where cars overtake cyclists. Instead of “nobody cycles there anyway”, you show how cycling has developed since the street was redesigned.

That comparison works best if you start early. A measurement before the redesign gives you a baseline; a measurement afterwards shows the effect. After that, it pays to keep measuring: behaviour changes gradually, and an intervention that looks good after a month can look different after a year. Data also make visible what is going well. A bicycle zone that works deserves to be the model for the next one.

From measuring to acting

Measuring is not a goal in itself. The value lies in what you do with it. If cars regularly overtake cyclists at certain times, an extra design measure or targeted enforcement helps. It is also a sign that the street is being used as a through route. And if the number of cyclists clearly rises, you have a strong case for extending the network.

What matters is that the figures make sense to everyone. A dashboard that shows how each street is doing over time makes it easier to explain decisions to the mayor and aldermen, the council and the neighbourhood.

Data also let you compare bicycle zones with each other. Why does one street work better than another? Is it the width, its role in the network or the signage? By measuring the same indicators across several locations, you learn what makes a good bicycle zone, and you carry those lessons into the next design.

What about privacy?

A fair question for any camera in public space. Monitoring needs movements, not people. That is why faces and number plates are blurred and the system delivers anonymised counts and movement patterns, not identifiable people. It is designed around the GDPR.

Want to know how your bicycle zones are performing? Start with the question you want answered. That question determines the right measurements.