New expert article: Local public transport data for environmentally sensitive mobility management
In her latest article in Urban Transport Magazine, Dr Christine Langhanns (rms GmbH) demonstrates how data from local public transport plays a key role in environmentally sensitive mobility management. She explains how timetable, real-time and operational data support digital passenger information, improve traffic simulations and enable AI-based forecasts and adaptive control strategies.
The article illustrates that the impact within the overall system can only be fully realised if public transport data is linked with traffic, environmental and weather data. Standardised data formats such as GTFS and NeTEx, as well as precise geographical stop information, create the necessary conditions for this.
Examples from the AIAMO pilot regions of Leipzig and Landau in the Palatinate demonstrate how public transport data is used in practice: in Leipzig, real-time forecasts from Leipziger Verkehrsbetriebe are evaluated on the basis of operational data and processed for AI applications. In Landau, timetable and real-time data from regional transport services are combined with traffic count data to predict barrier closures and proactively adjust traffic light controls.
This article demonstrates that public transport data is a key component of connected, intermodal and environmentally sensitive mobility. By integrating this data into digital twins and AI-based forecasting models, it is possible to model transport flows more realistically, plan measures proactively and further improve the quality of public transport.
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