ARIC Brown Bag Session: AI for Railway Passenger Forecasting

This talk will be held in English!

Estimating the demand of future railway travel is essential to set adequate prices in rail travel, lowering prices to increase acceptance during off-peaks, and eliminating super saver prices during peaks where overcrowding can ocurr. Special calendar event, from one-time daily events like Taylor Swift concerts, to reocuring special events like premier league football, concerts, Christmas markets, as well as seasonal travel to seaside and weekend short-trip destinations pose particular challenges to setting effective prices. We present a case study from iqast at the UK rail FutureLabs accelerator, where we applied fully-automatic AI forecasting models with advanced feature engineering, lowering forecast errors during events and raising revenue significantly by settting improved prices for 2 UK railway train operating companies.
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Dieses Format wird im Rahmen des EDIH Hamburg, mit Unterstützung durch die Europäische Union und der Hamburgischen Investitions- und Förderbank angeboten. #EDIHHamburg