ReMuNet
Financiado
Resilient Multimodal freight Transport Network
ReMuNet identifies and signals disruptive events and assesses their impact on multimodal transport corridors. It reacts quickly and seamlessly upon disruptive events in real-time. It supports TMS-providers to improve route plannin...
ReMuNet identifies and signals disruptive events and assesses their impact on multimodal transport corridors. It reacts quickly and seamlessly upon disruptive events in real-time. It supports TMS-providers to improve route planning resilience. ReMuNet communicates alternative, pre-defined, multimodal transport routes to logistics operators and subsequently to truck drivers, locomotive drivers and barge captains. Through this, it enables a faster and adaptive multimodal network response. ReMuNet orchestrates route utilization, suggests transshipment points and optimizes capacity allocation, minimizing damage and shortening the recovery time. What is ReMuNet’s core objective?As trailblazer for the Physical Internet, ReMuNet pursues the vision to enable and incentivize synchro-modal relay-transport on European rail, road, and inland waterways to increase the holistic network resilience. It significantly reduces emissions and boosts freight transport corridor efficiency in case of disruptive events. How will ReMuNet achieve this?1.A standardized method to describe multimodal transport networks. The proposed standard is derived from existing approaches and developed together with critical stakeholders to ensure Europe-wide practicability and acceptance2.An algorithm capable of calculating multimodal route alternatives and capacity utilization in the face of disruptive events. It uses real-time data for dynamic synchromodal alternative route planning 3.A collaborative platform connecting relevant freight operators and enables them to manage disruptions. This is done by providing secure and resilient digital logistic and network management tools enabling alternative route planning information and orchestrating event-based synchromodal relay transportation 4.Using Reinforcement Learning to model and evaluate alternative courses of action, providing the basis for a self-learning, adaptive multimodal European freight transport and logistics network
ver más
Duración del proyecto: 35 meses
Fecha Inicio: 2023-07-01
Fecha Fin: 2026-06-30
Fecha Fin: 2026-06-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-07-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
4M€
Líder del proyecto
FIR E.V. AN DER RWTH AACHEN
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5