12.11.2026

From Passenger Counting to Representative Sampling: App-Based Mobility Data

With the introduction of the Deutschlandticket, the need to capture actual public transport usage across transport association boundaries has increased. In the latest issue of the professional magazine NahverkehrsPraxis (9–10/2026), Prof. Dr.-Ing. Uwe Plank-Wiedenbeck of Bauhaus-Universität Weimar and Dipl.-Phys. Thomas Hornig, Managing Director of highQ Computerlösungen GmbH, explain how smartphone-based mobility data can be used cost-effectively and on a statistically sound basis.

In their article the authors present a method in which randomly selected passengers have their journeys recorded via a smartphone app. Algorithms identify the routes travelled and modes of transport used. Statistical extrapolation of these data provides insights into which public transport operators are used and to what extent. This creates a basis for distributing Deutschlandticket revenues among participating operators according to actual usage. Combined with automated passenger counting systems and targeted surveys, this hybrid model can also reduce data collection costs.

The research project AIAMO – Artificial Intelligence And MObility contributes the data integration and AI architecture AIAMOnexus to support the further development of this approach. It can integrate, harmonise and quality-assure app-based mobility data alongside other data sources. The European Digital Innovation Hub MID Germany supports testing, knowledge transfer and scaling to facilitate adoption by municipalities and transport operators.

The article demonstrates how statistical methods, digital mobility tracking and AI-powered data integration can be combined to improve the data available to public transport operators and transport associations.

Read the full article: “From Passenger Counting to Representative Sampling – App-Based Mobility Tracking as a Cost-Effective Data Source,” NahverkehrsPraxis, Issue 9–10/2026 (PDF)