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Case studies

Use big data to detect parking behaviour

The Kortrijk case focuses on integrated parking management. In Kortrijk, more than 1000 on-street parking spots are equipped with a dedicated parking sensor, which registers the status of the parking places. Besides the 1000 on-street parking sensors also open and live data is available of all the public parking garages and terrains.

In the city centre, it is only allowed to park your car for a half-hour on one of the 1000 so-called ‘shop & go’ parking places. Parking sensors monitor the actual status, and the parking attendants can monitor real-time where cars are in overstay. The same sensors can be used to monitor the behaviour in the other parking zones (with a maximum stay of 2 hours) in the city. By using a statistically relevant sample, the current parking policy in the city centre can be scrutinized in more detail.  

The Kortrijk case will provide insight into how advanced sensors can be used for policymaking and policy measuring. By combining the relation between different sensors, AI can be used to predict the most efficiënt parking policy to support a livable city and to support the local economy.

This case was in the end not worked out in Polivisu.

Challenges encountered:

Expected  challenges

  • The PoliVisu Kortrijk case leans on years of experience with (automated) parking management of the Kortrijk City parking company Parko.
  • The first challenge we will encounter is to get a better insight into the parking behaviour in the 2 hours zone. It’s important to check the number of cars in overstay (parking more than 2 hours) and the unpaid parking places.
  • A second challenge is to get an idea of the parking pressure and the impact on overstay.
  • The third challenge is to define and test a prediction model for parking pressure based on historical data.

Stakeholders:

  • Parko (Kortrijk city owned parking company)
  • City of Kortrijk
  • Geosparc
  • Informatie Vlaanderen

Actions steps:

Defining clear research questions (policy preparation) and defining of a first scientific approach to have a qualitative sensor test sample.

Lessons learned:

As we did not continue with the case, this is not relevant

Outcome impact:

As we did not continue with the case, this is not relevant

Links:

 

 


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