A standardized approach for describing multimodal transportation networks has been developed through collaboration with key stakeholders to ensure its practicality and acceptance across Europe. This standard can be seamlessly integrated into regulatory frameworks to enhance communication and connectivity among operational stakeholders.

An algorithm capable of computing alternative routes and assessing capacity utilization in the presence of disruptive events (such as pandemics, natural disasters, geopolitical conflicts, or construction sites) uses real-time data for dynamic synchromodal route planning.

A collaborative platform connects relevant logistics operators, providing them with secure digital tools for managing disruptions. This platform facilitates alternative route planning and coordinates event-driven synchromodal relay transportation.

Utilizing AI, specifically Reinforcement Learning, to model and assess alternative courses of action lays the foundation for a self-improving, adaptable multimodal European freight transport and logistics network. This approach enhances the resilience of European trade.