Combined road/rail freight transport (CT) is becoming increasingly important, because only a combination of transport modes can sustainably handle the constantly growing volume of goods. Artificial intelligence (AI) and data-driven planning cannot be missing from this development, of course. Prof. Ralf Elbert and our research associate Yuerui Tang explain in an article in the latest issue of International Transport how AI and loading optimization can support CT and thus the achievement of climate targets.

We already know that CT emits up to 90% less CO2 compared to pure road transport – and by using AI, we can increase the efficiency of this system and thus contribute to a more sustainable future. Because CT combines the best of both worlds: the environmental sustainability of rail and the flexibility of road.

Learn more about how we can change CT sustainably with the research project KIBA .

This research project is funded by the German Federal Ministry of Digital and Transport based on a resolution of the German Bundestag.