VSB-ÖP

Contact: Dipl.-Inf. Christine Keller

How can the data quality in public transport be recorded and improved so that travel by bus and train runs more smoothly? This question is being investigated by the research project "VSB-ÖP (Reliability of Smart and Big Data in Public Passenger Transport)"

In public passenger transport (PT), a lot of different data is generated from a wide variety of data sources. Among other things, departure and arrival times, standing times, positions of individual vehicles, number of passengers, breakdowns and disruptions are recorded. The aim of this research project is to collect and improve the quality of the data, in order to build on it to evaluate the data with Smart and Big Data technologies and thus improve the quality of public transport in the long term. Data quality is important because decisions are made and planning is done on the basis of the data collected.

Big and Smart Data approaches to optimize planning in public transport

This is done by capturing the origin and processing chain of the data in a semantically rich model and providing it as metadata. Based on this, Big Data and Smart Data approaches are used and planning is optimized. The researched methods will be tested in the project for their applicability in real-time on real-time data. The goal is to be able to react as quickly as possible to unpredictable events. Through the advanced use of public transport data and its evaluation with Big Data and Smart Data technologies, transport operators will be enabled to find and eliminate causes for incorrect planning and incorrect journeys, to identify causes for disruptions in the operational process and exceptional situations and to react to them.

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The research project is funded by the German Federal Ministry of Education and Research (BMBF) until 2021. Furthermore, init GmbH is contributing financial resources to the project, in addition to its 35 years of experience in IT solutions for transportation and traffic. From the results, those involved are hoping for new insights for data processing and optimization and thus for customers stress-free and punctual journeys in public transport.