Data-driven: getting a picture of driving behaviour in the Defence department’s official vehicles

Use case Defence
Over recent years, sustainability has become an increasingly important theme in the Defence department in the Netherlands. The non-military cars used by the PNOD (the service’s pool of non-operational vehicles) for Defence department staff is currently making efforts to make the driving ‘cleaner and greener’. To promote such driving behaviour, an integrated mobility policy is being developed that encourages staff to think more about their choice of mode of transport.

Developing that kind of policy needs a thorough understanding of current driving conduct. To achieve that, the Datalab of the JIVC (the Defence department’s Joint Information Provision Command) has carried out a successful research project.

Purpose of the project

This project aimed to get a clear picture of how sustainably the official cars were being used. How often are official vehicles being driven short distances, for instance? Or used for routes where good public transport links are available? And how often are official vehicles left unused for lengthy periods when there are not enough at other locations to meet demand? To answer questions like these, the Datalab has developed a dashboard that makes it easy to query data about the official cars.

Offering a visual overview

This solution lets the client select locations, time intervals and journey distances themselves and then call up the statistics and visualisations that provide the desired insights. With the help of artificial intelligence, for instance, this lets them extract clear pictures quickly and efficiently from the large quantity of data that the PNOD dataset contains.

From insight to policy

The understandings generated by the dashboard can be used by policymakers. For instance, if it turns out that official cars are used particularly often for driving between nearby barracks, it could for example be possible to provide electric bicycles at that location to encourage people to cycle the distance of (say) four kilometres. Data-driven insights can then help policymaking and ultimately reduce CO2 emissions.

Parties involved:

  • DOSCO (Defence Support Command)
  • DMO (Defence Materiel Organisation)
  • JIVC (Joint Information Provision Command)
  • KIXS (Knowledge, Innovation, eXperiments, Simulation)
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