As of 2018, the entire transport sector has been accounting for 21% of global CO2 emissions, and road-bound freight traffic has been accounting for almost 30% thereof. [2] Furthermore, global freight traffic demand is expected to triple between 2015 and 2050 [1]. If current and announced mitigation policies are implemented, the CO2 footprint of worldwide transport is expected to increase by 60% by 2050, mainly driven by non-passenger and freight traffic. In an optimistic and highly ambitious scenario, the CO2 footprint is only expected to remain relatively stable until 2050, which would still be insufficient to achieve the Paris Agreement for a below 2 degrees Celsius temperature increase above the pre-industrial era.

What is thus needed are novel and innovative solutions in all areas related to freight traffic, including prominent directions such as the development of more efficient and carbon-saving propulsion systems, or an increase of the modal split of rail in the entire transport system. However, also the potential impact of less high-profile issues should not be underestimated. For instance, the share of empty truck journeys in Austria has increased from 31% to 45% between 2010 and 2019 [3], suggesting a substantial potential for optimisation and carbon-savings.

A key approach to improving the situation is to establish a sharing economy in the logistics industry: while today logistics companies only carry out internal optimisations with regard to resource utilisation, increasing digitalisation also offers the opportunity to carry out cross-company optimisations and resource allocation. Such optimisations would allow to increase the average load factor of transport providers, thereby decreasing empty runs, traffic volume, costs, and ultimately reducing the overall carbon footprint of the entire transport sector.

However, when competitors could share resources beyond company boundaries, they often have concerns about confidentiality as, for example, the individual cost structure is sensitive and contains trade secrets. This leads logistics companies not to participate as the leaked information could be used against them by competitors.

The vision of MUPOL is thus to analyse the feasibility, and lay the foundations, for a framework allowing for secure multi-party optimization in the logistics sector. In this framework, transport providers will be able to contribute their transport tasks (including detailed descriptions regarding source and destination, volume, time constraints, etc.) as well as their available resources (together with all relevant constraints). The framework would then compute a (nearly) optimal assignment of orders to logistic providers, minimizing predefined parameters (such as empty runs, expected fuel consumption, etc.) within mutually agreed perimeters (e.g., ensuring that all participants receive a fair fraction of orders).

Incorporating advanced cryptographic mechanisms such as multi-party computation or fully homomorphic encryption, potentially combined with distributed optimization algorithms, this framework will ensure that no participant needs to reveal any sensitive business information to any other participant in the system, including any third parties or brokers, thereby immediately overcoming the companies’ reluctance to participate. The MUPOL framework is envisioned to be transport-medium agnostic, thus being open to regional logistic providers covering the first/last mile, as well as transregional providers such as heavy good vehicles or rail cargo.

• Partner: Fraunhofer Austria Research Gesellschaft mit beschränkter Haftung (Koordinator), Lakeside Labs GmbH, AIT Austrian Institute of Technology GmbH
• Förderprogramm: Digitale Technologien 2022, Sondierung
• Projektlaufzeit: 11/2023-10/2024