Transport planning and fare allocation in public transport rely on one key element: reliable data that reflects how people actually move. For decades, this information has been gathered through traditional surveys requiring extensive personnel, long preparation times, and results that capture only a brief moment in time.
But what if mobility data could be collected continuously, updated daily, and with significantly less effort?
This is exactly what BVG and motiontag are exploring in the project NuVe – Nutzerunterstützte Verkehrserhebung (User-Assisted Traffic Survey).
A new approach: capturing mobility data via smartphones in a privacy-compliant way
For the project, motiontag’s detection technology was integrated into the BVG Fahrinfo app. The concept is easy to explain: the app automatically detects movements and modes of transport in the background, of course only with explicit user consent and in full compliance with data protection regulations.
For users, not much changes. For transport operators, however, the potential impact is substantial. Instead of isolated survey snapshots, they gain a continuous and nuanced picture of actual usage patterns.
Impressive participation and data that closely matches real-world figures
Since the start in May 2025, around 28,000 people have registered for the project (as of May – October 2025). Their trips amount to a dataset of more than 2.5 million recorded segments. This includes numerous public transport journeys where the detected movement can be directly linked to a ticket.
The comparison with existing datasets is particularly compelling:
Comparisons with UBF 2024 and Mobility in Cities (SrV 2023) show:
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Public transport trips (UBF) are captured almost exactly.
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Modal split (pkm) is also nearly identical for motorised transport (private cars and public transport).
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Only cycling and walking show differences, which can be explained by methodological variations.
Overall, the comparison confirms: the digital method captures the key indicators with high accuracy.
„The data is truly very plausible and also representative.“ – Stefan Geier, BVG
Why this approach is so promising
This methodology can have far-reaching implications for transport providers.
Not only would the effort decrease how data can be used would fundamentally change:
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No more dependency on survey years; instead, continuous insights into trends.
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Multimodal journeys, transfers, and regional differences would become visible in far more detail. Transport models and planning processes could be continuously calibrated to align decisions more closely with real-world usage.
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Decisions on planning, quality assurance, and fare allocation could be grounded more strongly in actual user behaviour.
And the fact that the technology is energy-efficient, precise, and privacy-compliant is not a side note, it is the key to making long-term data collection possible in the first place.
Conclusion: A project with signalling power
NuVe clearly demonstrates how advanced digital mobility data collection has become and the opportunities it brings for planning, managing, and funding public transport.
BVG and motiontag are not simply testing a technical feature.
They are piloting a potential future standard method that will allow transport providers to work more fairly, precisely, and efficiently.
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