KIBA artificial intelligence project underway: AI to optimize loading in combined transport

A new digitalization project in the combined transport space aims to speed up the allocation of intermodal transport units to rail freight wagons. Using suitable computation processes in conjunction with methods borrowed from artificial intelligence (AI), the objective is to optimize the loading of transport units on rail freight wagons. KIBA – the project’s full name is “Artificial Intelligence and Discrete Loading Optimization Models to Increase Capacity Utilization in Combined Transport” – was launched in early September 2022.

At the Federal Ministry for Digital and Transport in Berlin, Federal Minister Volker Wissing today presented the team with the official project certificate and wished them a successful start. The IT project is scheduled to run for three years, and Wissing’s ministry is sponsoring it to the tune of 2.34 million euros as part of the Artificial Intelligence in Mobility innovation initiative. Alongside Kombiverkehr Deutsche Gesellschaft für kombinierten Güterverkehr mbH & Co. KG, the company coordinating the project, the other project partners are the Technical University of Darmstadt, Deutsche Umschlaggesellschaft Schiene-Strasse (DUSS) mbH, Goethe University Frankfurt/Main, VTG Rail Europe GmbH, INFORM GmbH and KombiConsult GmbH. 

As things stand, combined transport across Europe uses a wide variety of transport unit types and rail freight wagons. The major challenge is therefore to optimize the allocation of transport units to rail freight wagons on a generally valid basis and as a function of different target sizes. The fixed technical characteristics of all kinds of semitrailers, containers, swap bodies and rail freight wagons naturally play an important part in this process. But so too do variable parameters such as the actual weight and nature of payloads, as well as freight timetables. The aim of the project is for every inquiry about the loading of a transport unit to be met as quickly as possible by a proposal that optimizes the positioning of the transport unit on the set of wagons deployed – and that at a time even before all information is available about what other transport units are yet to arrive at the shipping terminal for the same departure/destination constellation. In other words, AI-assisted loading optimization should facilitate advances in capacity management across intermodal operators and their extensive networks.

Joint Press Release: KIBA artificial intelligence project underway - AI to optimize loading in combined transport PDF


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