TruckInvest 4.0
Project objective
Development and use of machine learning methods for decision support in fleet-related investments.
The question of the most suitable vehicle for a prospective deployment profile is of fundamental importance in road haulage. From both a technical and a business perspective, transport companies must always ensure that future orders can be processed as profitably as possible with the vehicles purchased when making fleet-related investment decisions.
To date, however, this important question has been answered almost exclusively on the basis of experience and gut feeling. More precise approaches based on data cannot be found in practice, as the interplay of factors influencing costs is too complex.
As part of a joint project between the Saarland University of Applied Sciences (htw saar) and Qivalon GmbH, such approaches are now to be developed and transport companies are to be provided with a functioning tool to support them in their investment decisions.
The project entitled "TruckInvest 4.0" is being funded by the Federal Ministry of Transport and Digital Infrastructure as part of the mFUND research initiative. In addition to htw saar and Qivalon, the project consortium includes renowned companies from the logistics sector, which are available as data suppliers and test users and expect to see a sustainable reduction in costs for future investments.
Further objectives of the project are the economic evaluation of fuel-saving measures and the enrichment of the road network with consumption data.
October 01, 2017 until September 30, 2018
Funding program: mFUND (BMVI)
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