Funding source

July 2023 – June 2026

Project URL

Project information
Thematic keywords

  • Transport engineering
  • Multimodal transport
  • Resilient supply chain
  • Disruptive event
  • Relay-traffic
  • Synchro-modal, sustainable transport
  • Collaboration platform
  • Route planning algorithm
  • Self-learning impact modeling

ReMuNet’s primary focus is to identify and indicate disruptive occurrences, evaluating their influence on multimodal transport corridors. The system swiftly and smoothly responds to such incidents in real-time, aiding TMS providers in enhancing the resilience of route planning. ReMuNet communicates predefined alternative multimodal transport paths to logistics operators and subsequently to truck, locomotive, and barge operators. Through this, it facilitates a more rapid and adaptable response within the multimodal network. ReMuNet orchestrates route optimization, recommends transshipment points, and optimizes capacity distribution, ultimately minimizing damage and reducing recovery time.

The central objective of ReMuNet lies in being a pioneer of the Physical Internet concept. It strives to enable and incentivize synchro-modal relay transportation across European rail, road, and inland waterways, thereby enhancing overall network resilience. This, in turn, leads to a substantial reduction in emissions and a notable enhancement in the efficiency of freight transport corridors, particularly during disruptions.

To achieve these goals, ReMuNet adopts the following strategies:
1. Development of a standardized method for describing multimodal transport networks. The proposed standard is formulated collaboratively with key stakeholders to ensure practicality and acceptance on a Europe-wide scale.
2. Implementation of an algorithm capable of calculating alternate multimodal routes and assessing capacity usage in response to disruptive events. This algorithm employs real-time data for dynamic synchromodal route planning.
3. Creation of a collaborative platform linking relevant freight operators, providing secure digital tools for managing disruptions. This platform facilitates the exchange of alternative route planning information and orchestrates event-based synchromodal relay transportation.
4. Utilization of Reinforcement Learning to model and assess alternative courses of action. This forms the basis for a self-learning, adaptive multimodal European freight transport and logistics network.

We are responsible for the design and implementation of the communication and dissemination strategy and the project’s communication activities, we will manage knowledge, protect Intellectual Property Rights, and develop plans for long-term asset exploitation.