© Andreas Wiese

Modern transportation driven by artificial intelligence

The Ferdinand Steinbeis Institute builds a collaborative data space with Düsseldorf Airport

Imagine arriving at your business meeting just a few minutes after getting off the plane. The SkyTrain takes you to and from the train station, straight from gate to platform and back again. This is travel made easy thanks to a seamlessly connected, meticulously coordinated transportation network – no more queues, goodbye traffic jams. Düsseldorf Airport wants to make this vision of seamless transportation come true. With this in mind, the airport launched a pilot project with the Ferdinand Steinbeis Institute aimed at strengthening digital collaboration between carriers and identifying ways in which artificial intelligence can help to enhance public transportation services. Funded through the Ministry of the Environment, Nature Conservation and Transport of the State of North Rhine-Westphalia’s “Mobility as a Service NRW” initiative, the project developed a collaborative data space known as the “SkyTrain Data Space”. The shared data on timetables, delays, passenger numbers and flights accessed through the integrated data platform can be used to improve local public transportation services and enable more sustainable and cost-efficient operation of the transportation system.

Düsseldorf Airport wants to make its passengers’ arrivals and departures as convenient and fast as possible. This means enabling flexible switching between local and long-distance transportation services and different carriers. At the airport, national and international flight connections, light rail and bus services, and S-Bahn and long-distance trains are accompanied by an innovative infrastructure for individual transportation. EV charging stations right next to the SkyTrain station and an e-scooter and e-bike sharing hub are all within easy reach for anyone visiting the airport. Düsseldorf Airport is already exploring new ways of fulfilling its responsibilities as an intermodal hub – and is systematically leveraging the potential of digital technology to do so.

Collaboration based on shared data

So what does it take to effectively manage passenger flows at a transportation hub like Düsseldorf Airport? And how do you deliver a comfortable, seamless travel experience that is also efficient and sustainable? Collaboration between the different carriers is key to answering these questions. That’s why Siemens Mobility, Deutsche Bahn, Verkehrsverbund Rhein-Ruhr, DELFI and XOVIS are all partners in the pilot project jointly initiated by Düsseldorf Airport and the Ferdinand Steinbeis Institute.

At the heart of the pilot project is the SkyTrain, a driverless suspension railway system that every year shuttles millions of people between the nearby long-distance train station and parking facilities and the airport terminals. The aim of the project was to create an operational network among the partner carriers and bring together the relevant data in a collaborative data space. The data enables new digital services that improve the passenger experience and optimize the SkyTrain’s sustainability and cost-efficiency. The “SkyTrain Data Space” provides a platform for sharing data to create new digital services. It is also a trusted space where the partners can establish and strengthen business and data sharing relationships among themselves.

Adding value through collaborative data spaces

The airport uses digital technologies like people counting sensors at the SkyTrain stops to capture information about how full the trains and individual cars are at any given time, while the rail transit partners share operational data. Timetables, delay announcements, station stop times, train cancellations and waiting times are all fed into a collaborative data space that is also connected to regional and national transportation data systems in Germany. Over the course of the project, an AI-powered learning architecture identified concrete ideas for improvements in areas such as resource scheduling, energy management and passenger communication. If a train breaks down on the outskirts of a city or a maintenance depot doesn’t have the spare part it needs, the platform’s partners can work together to ensure that this does not cause long waiting times or avoidable empty runs elsewhere in the complex system. In the medium term, the aim is to create an entire ecosystem that enables the development of new AI services and is open to additional partners. The shared data thus provides the basis for data-driven services that transcend the parts of a journey covered by individual carriers and are focused instead on getting passengers to their actual destination. The project’s successful conclusion is just the starting point for closer cooperation between the different partners and for the incremental expansion of the digital services on offer.

Learning from data streams to deliver seamless travel

The first digital service served to predict passenger numbers on the SkyTrain. Different data sources from several partner companies were combined to enable AI-powered passenger number forecasting. This enables data-driven optimization of SkyTrain car scheduling, ensuring a more comfortable experience for public transportation passengers at Düsseldorf Airport. Passengers receive relevant up-to-the-minute information to help them plan their journey so that, throughout their journey, they always know if they will arrive at their destination on time. For example, before a train arrives at the long-distance train station, passengers are informed in good time about the remaining journey time to their departure gate, including the current waiting times at the security checkpoints.

Data from the collaborative data space was used to enable more accurate passenger number forecasting. Access to the partners’ current data, for example actual train departure/arrival times and passenger numbers, enables more accurate forecasting of future passenger peaks. This allows the participating carriers to tailor the capacity they provide to what is actually required so that capacity utilization is optimized.

The “SkyTrain Data Space” project at Düsseldorf Airport illustrates how data-driven analysis can enable more sustainable and cost-efficient transportation while at the same time delivering an enhanced passenger experience. This is achieved by bringing together different data sources from multiple transportation actors and combining them with airport passenger capacity data to produce accurate forecasts. The project has laid the foundations for incremental optimization of the SkyTrain transportation system. Other potential uses for the “SkyTrain Data Space” include the provision of real-time arrival and departure information and access to the platform for multimodal travel solutions. “Artificial intelligence can help us to manage intermodal transportation more efficiently, and our SkyTrain Data Space is a collaborative data space that provides the blueprint”, concludes Uwe Groß, SkyTrain Operations Manager at Düsseldorf Airport.


Building collaborative data spaces

Research and business are currently testing various models for strengthening data sharing between different organizations.  The Ferdinand Steinbeis Institute is engaging in transfer-oriented research and pilot projects with businesses to trial value-added solutions and processes that can help organizations to develop collaborative, data-based value creation initiatives.

The Ferdinand Steinbeis Institute has observed that data sharing projects and collaborative value creation initiatives based on shared data frequently have to contend with all manner of reservations among those involved. As a result, the organizations’ plans to scale up the development of data-driven services never make it off the drawing board and into reality. The Ferdinand Steinbeis Institute is developing a framework for building collaborative data spaces that provides a tool for addressing reservations and helping organizations to implement data-based collaborations.

Contact

Prof. Dr. Daniel Werth (author)
Senior Research Fellow
Ferdinand Steinbeis Institute (Heilbronn)
https://ferdinand-steinbeis-institut.de

Maximilian Werling (author)
Research Assistant
Ferdinand Steinbeis Institute (Stuttgart)
https://ferdinand-steinbeis-institut.de

227255-20