A clear look ahead with real-time data

Large events at the Johan Cruijff Arena draw ten thousands of visitors. The nearby concert halls also regularly draw large crowds. How do you direct all of that traffic? It starts with monitoring. Real-time information about the situation on the road helps.

Insight into spectator flow

At peak times, it can get very busy around the Johan Cruijff ArenA. Large numbers of people make their way to a football match or to a concert by their favorite artist. Traffic jams are likely, so people arrive too late or have to wait a long time before they can return home. In order to prevent that, constant insight into spectator flow is important.

Annita Vijverberg

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Please feel free to contact us. Annita Vijverberg is our expert in this field.

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The solution

Current overview of the situation on the road

During crowded events, various parties - including road authorities, the police, parking operators and ArenA employees - gather in the Operational Mobility Center, a control room where they can closely monitor the traffic situation.

Geodan helps by collecting and visualizing all relevant traffic data in real time on an interactive screen. All of this data can be linked via an open sensor platform. For example: The data from the National Road Traffic Data Database shows all traffic jams and indicates whether - as with previous, similar situations - this may cause problems. In that case, the Operational Mobility Center may decide to open an additional lane.

It also makes clear, for example, which parking garages will fill up first. Road users can then be redirected to locations where there is still space via matrix signs. Camera images can show you the effect of the measure taken in retrospect. Machine learning - which involves automatically detecting new patterns in data - can also be used to predict future traffic situations. That’s very useful, because real problems usually only arise when the situation on the road deviates from known scenarios.

The result

Acting quickly together

Because all parties in the Operational Mobility Center have the same up-to-date traffic information at the same time, it creates a joint picture of the crowds on the road. This lets them better coordinate their measures and means road users will be less inconvenienced.

Machine learning can predict future traffic situations.

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