Swiss Federal Railways (SBB) want to tell their passengers which carriages have seats available. As the SBB partner for improving capacity planning, Zühlke uses machine learning to do just that.
Finding available seats more quickly
Due to a growing population and greater mobility, Swiss Federal Railways (SBB) have capacity issues. They want to optimise use of their existing infrastructure. Until now, the only occupancy forecast was based on classes of travel. The SBB want to break this down by individual carriages. This would make it quicker to identify which seats are available and would mean that passengers are more evenly distributed across all carriages. Zühlke is contributing to the project with its expertise in project management and data science.
Productive machine learning applications
A joint SBB and Zühlke team is developing an algorithm based on machine learning. Current data, such as feedback from the conductor, timetable information, group and individual seat reservations, public holiday dates, and weather forecasts are all being used. Zühlke is assisting with data processing, developing the algorithm and agile project management.
' SBB considers the project to be a complete success because, with Zühlke, we had the perfect partner on board. In addition to incredible expertise in project management and data science, Zühlke employees identified with the project, which created an excellent sense of team spirit that, in turn, was an important factor in the success.
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Seat availability as a USP
The ability to predict which carriages have available seats is a unique selling point for the SBB. The machine learning algorithm allows the SBB to optimise use of its fleet and plan more accurately. Passengers can locate available seats much more quickly, and the overall user experience is enhanced. Train punctuality also improves. The solution is integrated into the online timetable, the SBB app, and the passenger information displays on platforms.
