Imagine if shipping packages worked like the internet, where data packets find the fastest route automatically. This project does that for physical goods, using smart containers and AI to switch between ships, trains, and trucks seamlessly. It helps companies share space and vehicles to stop driving empty trucks and cut pollution.
Freight transport suffers from low capacity utilization and high carbon emissions due to fragmented data and rigid transport modes. This leads to increased costs and failure to meet climate targets.
A suite of AI algorithms, Digital Twins, and shared standardised containers for multimodal transport. These tools enable real-time switching between transport modes and resource pooling.
If you are a 3PL provider dealing with inefficient route planning and empty return trips — this project developed synchromodal algorithms and resource sharing models that increase capacity utilization across different transport modes.
If you are a port operator dealing with high carbon emissions and congestion — this project developed digital twins and automation systems that facilitate the use of zero emission vessels.
If you are a distribution company dealing with high costs of fragmented delivery networks — this project developed shared standardised boxes and collaborative data models that allow SMEs to participate in pooled logistics.
Based on available project data, specific pricing or implementation costs are not provided; the project focuses on ensuring networks remain cost effective and competitive.
Yes, the project aims to scale up collaborative solutions for multimodal nodes and reach TRL 7 by the end of the period.
Based on available project data, the project prioritizes open access definitions and the DTLF data sharing framework to ensure scalability.
The project supports the 2030 Climate Target Plan to reduce emissions by 55%.
The project runs from 2025-07-01 to 2028-12-31, aiming for a high readiness level by the end date.
The consortium is heavily weighted toward industrial application, with 19 industry partners representing 73% of the group. This high industry ratio, combined with 26 partners across 14 countries, suggests a strong focus on commercial viability and cross-border interoperability rather than pure academic research.
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