Cross-Border Mobility Data Space for Smart Communities

Turning existing mobility data into a clearer picture of traffic flows – without the need for additional physical sensors

Key Figures

2

Pilot Cities

7

Consortium Partners

3 months

Duration

€834 668,48

Budget

About OmniFlow

Mobility is constantly changing, but the data available to transport planners does not always keep pace. Traditional traffic counts and physical sensors provide valuable information, but their coverage is limited to specific locations and periods. This can leave municipalities with an incomplete picture of how their transport networks are being used.

OmniFlow explores a new approach to filling these information gaps. The project combines aggregated mobile network data with existing road sensor information to provide a broader understanding of traffic flows and mobility trends. The approach is designed to be privacy-compliant and focuses on overall movement patterns rather than individual journeys.

At the heart of OmniFlow is the virtual traffic sensor – a digital solution that can estimate vehicle flows at locations where no physical traffic sensor is installed. This could allow municipalities to gain insights into a much wider transport network without the need to install additional monitoring infrastructure at every location.

The approach will be piloted in Šiauliai, Lithuania, and Jelgava, Latvia, including their surrounding rural areas. By testing the solution in real-world conditions, OmniFlow aims to demonstrate how better mobility insights can support evidence-based transport planning, public transport optimisation, traffic management, and infrastructure investment – in cities as well as less densely monitored areas.

This project has received co-funding from the European Union’s Digital Europe programme under grant agreement No. 101123342. Total budget (including co-funding): 834 668,48 EUR.

How it Works

Step 4: Estimate vehicle flows

Step 2: Analyse mobility patterns

Step 3: Add existing road sensor data

A municipal user selects a location on the map and places a virtual traffic sensor there. No physical equipment needs to be installed at the selected location.

The selected location is matched with privacy-compliant, aggregated mobile network data to estimate the overall flow of people in that area. The data is statistically adjusted to provide a representative picture of mobility patterns

Where available, information from nearby physical traffic counting stations operated by national road authorities is added to complement the mobility data.

Step 1: Create a virtual sensor

The different data sources are combined and calibrated to distinguish vehicle traffic from other forms of movement, such as walking and cycling. This produces an estimated vehicle flow for the selected location

Step 5: Get actionable insights

The municipality receives an estimated number of vehicles per hour at the selected virtual sensor point. These insights can support transport planning, public transport demand analysis, infrastructure maintenance and prioritisation, and other mobility planning activities

Step 6: Validate the results

During the OmniFlow pilots, the estimates generated by the virtual sensors will be compared with physical traffic counts to assess their accuracy and reliability in real-world conditions