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FeDerated nEtwork of pLatforms for Passenger and freigHt Intermodality

Periodic Reporting for period 1 - DELPHI (FeDerated nEtwork of pLatforms for Passenger and freigHt Intermodality)

Reporting period: 2023-07-01 to 2024-12-31

The DELPHI project, titled "FeDerated nEtwork of pLatforms for Passenger and freigHt Intermodality," aims to develop a federated network of multimodal transport platforms that seamlessly integrate passenger and freight mobility systems. The project focuses on governance frameworks, data sharing, predictive modeling, and optimization techniques to improve efficiency and reduce emissions in urban and regional transport.



Efforts in standardization and policy recommendations have been crucial, ensuring compliance with EU regulations while promoting interoperability across transport systems. Dissemination activities included website development, scientific publications, and industry engagement to maximize project impact. Overall, DELPHI aims to enhance multimodal transport efficiency through innovative governance, technological advancements, and strategic stakeholder collaboration.
The DELPHI project, formally known as "FeDerated nEtwork of pLatforms for Passenger and freigHt Intermodality," is a European initiative focused on transforming combined passenger and freight transport through a federated network of platforms. The project addresses the challenges of integrating passenger and freight mobility systems by developing novel governance models, secure data-sharing frameworks, and optimization tools. By aligning with European regulatory standards and best practices, DELPHI seeks to create a seamless and efficient multimodal transport ecosystem that enhances interconnectivity, sustainability, and operational efficiency.

Throughout the reporting period, significant progress was made in key areas, including data management, compliance with legal and ethical standards, and the development of a technological framework for secure information exchange. A comprehensive Data Management Plan (DMP) was implemented, ensuring compliance with GDPR and FAIR data principles. The establishment of an Ethics Review Committee further strengthened the project's commitment to privacy, security, and transparency. Additionally, methodologies for safe and efficient data sharing were developed, incorporating best practices in data validation, encryption, and access control while maintaining alignment with GDPR and ISO standards.
An advancement in DELPHI was the design of optimization models for multimodal transport. Work Package 4 focused on developing predictive models that utilize machine learning techniques, clustering, and causal reasoning to enhance transport decision-making. These models aim to optimize freight and passenger flows, reduce emissions, and lower operational costs. Real-world data collection played a critical role in these efforts, with drone-based monitoring in Madrid and Mykonos providing insights into congestion patterns, vehicle behavior, and emissions estimation. In Athens, CO2 and noise sensors were deployed to assess environmental impacts, further supporting the optimization framework.

The validation of DELPHI’s proposed solutions began through a combination of real-world pilot studies and large-scale simulations. Four pilot sites—Mykonos, Athens, Cluj-Napoca, and Madrid—were selected to test the integration of passenger and freight transport in different urban and regional environments. The pilots focused on real-time traffic monitoring, secure data exchange, and predictive modeling to enhance operational efficiency. A simulation-based validation methodology was also established to assess the project’s scalability and effectiveness in handling complex transport scenarios involving thousands of vehicles and passengers.
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