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Operational automation to support multimodal freight transport

Automated vehicles, rolling stock and vessels, as well as related transhipment automated processes, are developed independently within the various transport modes and sectors. This creates gaps and disconnections in the actual use within the logistics operations, missing concrete new operational models and opportunities for end-to-end logistics, which may support adoption and contributing to system integration and decarbonisation.

Automation will change the way goods flow across all modes (possibly encouraging modal shifts to coastal shipping modes/smaller vessel fleets, inland waterways transport, railway transport, or alternative road transport usages) and is not well explored in terms of opportunities for the logistics supply chains and enabling increased usage of vehicles and infrastructures. A high level of operational automation can be reached in terminals and hubs (e.g. node-to-node operations undertaken in inland hubs, multimodal depots, logistics terminals, freight consolidation facilities), which offer controlled environments and repeatable processes but also in the operational domain of processes occurring in those places.

To ensure operational efficiency and support multimodal transport, proposals should address all the following points:

  • Identify gaps in automated transport technologies and logistics operations between modes and hubs.
  • Assess benefits of autonomous vehicles, rolling stock and vessels to multimodal logistics and the role/benefits of seamless multimodal automatic cargo transport across transport modes (rail, road, waterborne, aviation, alternative innovative modes of transport).
  • Investigate the requirements and define concrete benefits of seamless and automated logistics operations, particularly in multimodal terminals and hubs, linking e.g. rail, road and inland waterways with a focus on intra-European freight flows. Consider interoperability and cybersecurity issues.
  • With the support of e.g. machine learning, digital twins, robotic process automation and AI, and using historical operational data, compare and demonstrate (through simulation) benefits of operational automation to current standard flows and operations in all modes. Synergies for rail will need to be sought with the EU-Rail Programme projects implementing the Flagship Areas 1, 2 and Destination 5[[ See draft EU-Rail Multi Annual Work programme at https://shift2rail.org/wp-content/uploads/2021/12/20211222_mawp_v1_agreed-in-principle_clean.pdf]].
  • Design, analyse and evaluate business and governance models as well as organisational change issues and incentives to reduce the investment costs and support the implementation of automated solutions for logistics and multimodal freight transport.
  • Develop and propose recommendations for possible regulatory and policy actions supporting the adoption of automated solutions for logistics and multimodal freight transport.

If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries are expected to clearly describe if and how the use of Copernicus and/or Galileo/EGNOS are incorporated in the proposed solutions. In addition, if the activities proposed involve the use and/or development of AI-based systems and/or techniques, the technical and social robustness of the proposed systems has to be described in the proposal.