Project Description
AI for Resilient Rail Corridors: Critical Freight and Military Mobility is a research project developed within the framework of a
six-month Hosting Commitment at ERCI – European Railway Clusters Initiative ASBL, from 1 February to 31 July 2026, as part of the PhD programme in Big Data and Artificial Intelligence. The research investigated the strategic role of European rail corridors in ensuring supply chain continuity, protecting critical freight flows, and supporting military mobility.
The project addressed rail resilience as a
socio-technical and decision-making challenge, in which physical infrastructure, transport capacity, operational data, digital systems, governance, and artificial intelligence must operate in an integrated manner. Particular attention was devoted to capacity allocation mechanisms, reserve and contingency train paths, real-time monitoring, and predictive disruption management.
The research is positioned within the broader European framework of
industrial resilience and strategic autonomy, considering rail corridors as dual-use infrastructure required to ensure both the continuity of essential civilian flows — including critical raw materials, semiconductors, energy equipment, and essential medical and chemical products — and the requirements of military mobility.
The research project consistently addressed the priorities of
LEADER 2030, a project funded within the framework of Europe’s Rail JU and aimed at strengthening the capacity, autonomy, and resilience of the European rail value chain towards 2030.
Description of the Activities Carried Out
Over the six-month period at ERCI – European Railway Clusters Initiative ASBL, I developed an interdisciplinary research pathway spanning transport engineering, artificial intelligence, cybersecurity, governance, and industrial resilience, with the objective of investigating how to strengthen the capacity of European rail corridors to ensure the continuity of strategic flows under crisis or disruption conditions.
I focused my research on integrating critical freight and military mobility requirements into rail capacity management mechanisms, examining the use of reserve capacity and contingency train paths, priority management, cross-border coordination, and the strengthening of corridor-level governance.
A central part of my work focused on the use of Artificial Intelligence to support decision-making processes. I developed a decision architecture capable of connecting operational events, performance indicators, predictive analytics, and decision-making responsibilities, transforming real-time monitoring from a simple visibility tool into a component of a decision infrastructure for anticipatory disruption management. Within this model, AI operates according to a human-in-the-loop approach, preserving human authority over decisions concerning priorities, capacity reallocation, and emergency interventions.
I also investigated the cyber-physical resilience of dual-use infrastructure, linking rail networks, critical supply chains, digital systems, and the continuity of civilian and military operations.
Finally, I complemented the research with scientific output, participation in international conferences, and engagement with European initiatives and stakeholders, progressively assessing the results against emerging priorities in rail resilience, strategic autonomy, and military mobility.
Contribution to the LEADER 2030 Project
As part of my collaboration with
ERCI, I developed my research activities in close connection with
LEADER 2030 – Learnings for European Autonomy to Deliver Europe’s Rail in 2030, a project funded by
Horizon Europe through Europe’s Rail Joint Undertaking, focused on the resilience of the European rail value chain, the availability of critical raw materials and strategic components, and the reduction of critical dependencies.
In March 2026, through a Position Paper, I contributed to the validation and integration process of the final recommendations of the LEADER 2030 project. The contribution was incorporated into Deliverable D4.2 as part of the consultation and Validation Rounds conducted with stakeholders between January and March 2026.
My contribution focused particularly on Recommendation
E.1 – “Ensure regular flows of critical industrial supplies along EU Rail Corridors”, examining the technological and decision-making conditions required for rail corridors to ensure the continuity of flows of critical raw materials, semiconductors, and other strategic goods.
The institutional relevance of this contribution is further reinforced by the trajectory of
Deliverable D4.2: the final recommendations of LEADER 2030 were presented on 8 April 2026 at the European Parliament in Brussels, as part of the project’s final event, thereby contributing to the European-level debate on strategies for the resilience and autonomy of the rail value chain
.
The Deliverable was also formally received by the European Commission and Europe’s Rail Joint Undertaking.
My contribution therefore forms part of a development and validation process directly involving European Union institutions and stakeholders.
Building on this framework, I developed a
multi-level decision architecture to address the
monitoring-to-decision gap, linking operational events, resilience KPIs, AI-based predictive analytics, and formally defined decision-making responsibilities.
My work thus contributed to connecting the strategic recommendations of LEADER 2030 with a potential
AI-enabled operational framework, aimed at translating industrial resilience, strategic autonomy, and logistics continuity into capabilities that can be concretely integrated into the governance of European rail corridors.
Scientific Output Produced
Over the six-month period at ERCI – European Railway Clusters Initiative ASBL, I progressively transformed the themes developed through my research into scientific contributions submitted to the scrutiny of the international academic community, focusing on the integration of Artificial Intelligence, rail resilience, critical infrastructure, and military mobility.
A first outcome was the paper “Real-Time Corridor Performance Monitoring for Critical Freight: An AI-Enabled Decision-Architecture Framework for Predictive Disruption Management”, which I presented as a speaker in May 2026 at the International Conference for Innovations in Intelligent Computing and Cybersecurity (IICC 2026) in Cairo and which was subsequently published in the IEEE Conference Proceedings and indexed in Scopus. In this work, I contributed to the development of an AI-enabled decision architecture that connects operational monitoring, KPIs, predictive analytics, and governance while maintaining a human-in-the-loop approach.
I also contributed as an author and speaker to the paper “Secure and Resilient Cyber-Physical Supply Networks for Critical Infrastructure: A Design Framework for Military Mobility and Mission-Critical Operations”, presented in July 2026 at the 17th International Conference on Ubiquitous and Future Networks (ICUFN 2026) at Politecnico di Milano and subsequently published in the IEEE Conference Proceedings and indexed in Scopus. The paper proposes a framework for resilient cyber-physical supply networks, applied to dual-use rail infrastructure and mission-critical operations.
Finally, I used my participation in the International Railway Summit 14 in London and the European Defence & Security Summit in Brussels as opportunities to compare and discuss the research findings in relation to European priorities concerning infrastructure resilience, interoperability, supply chain security, strategic autonomy, and military mobility.
IICC 2026
Maciariello, F., Benelli, F., Lorenzi, E., Bocci, V. E., & Salvadori, C. (2026). Real-time corridor performance monitoring for critical freight: An AI-enabled decision-architecture framework for predictive disruption management. In 2026 ICEENG International Conference for Innovations in Intelligent Computing and Cybersecurity (IICC) (pp. 1–6). IEEE. [https://doi.org/10.1109/IICC69623.2026.11582484](https://doi.org/10.1109/IICC69623.2026.11582484)
ICUFN 2026
Maciariello, F., Benelli, F., Bocci, V. E., Lorenzi, E., & Salvadori, C. (2026). Secure and resilient cyber-physical supply networks for critical infrastructure: A design framework for military mobility and mission-critical operations. In 2026 Seventeenth International Conference on Ubiquitous and Future Networks (ICUFN) (pp. 533–538). IEEE. [https://doi.org/10.1109/ICUFN69619.2026.11628810](https://doi.org/10.1109/ICUFN69619.2026.11628810)
Results Achieved
At the end of the six-month period at ERCI – European Railway Clusters Initiative ASBL, I consolidated a research pathway that produced results across three closely interconnected dimensions: scientific, methodological, and institutional.
At the scientific level, I developed and validated through international academic exchange two complementary frameworks: an AI-enabled decision architecture for monitoring and predictive disruption management in rail corridors, and a model for the resilience of cyber-physical supply networks applied to critical and dual-use infrastructure and military mobility.
At the methodological level, I contributed to redefining the rail corridor not merely as physical infrastructure, but as a socio-technical decision system, in which operational data, KPIs, predictive analytics, intervention thresholds, and decision-making responsibilities jointly contribute to overall resilience. Within this framework, I addressed the monitoring-to-decision gap, proposing a model in which AI supports the anticipation of critical events while preserving transparency, traceability, and human control over decision-making.
At the European level, I contributed to the validation and integration of the final LEADER 2030 recommendations, providing further insights into Recommendation E.1 concerning the continuity of critical industrial flows along EU rail corridors.
The overall result is an integrated research framework connecting AI, critical freight, cyber-physical resilience, military mobility, corridor governance, and European strategic autonomy, providing a methodological foundation for further research, validation, and project development activities at the European level.
Further Information on the LEADER 2030 Project
