FeDerated nEtwork of pLatforms for Passenger and freigHt Intermodality

Challenge & Objectives In both passenger and freight mobility, growing challenges are identified, such as urbanization trends, the increasing complexity of stakeholder scene, e-commerce and rising fragmentation of freight transport. Despite the various technical challenges, current governance and regulatory systems have proven so far inadequate, dealing with the passengers and freight transport systems as independent -and thus disconnected- sectors; at the same time, such operations share space, infrastructure, and challenges. Besides the above, integration between passenger and freight transport has been a subject of debate in the transport community over the last years with a peak coming after the recent Covid19 crisis. Considering the relatively recent interest in the topic, a lack – and at the same time urgent need – for common approaches and methodologies on the one hand, and seamless – and at the same time highly secure – data sharing is identified as the key way-forward.

DELPHI focuses on the strategic dimension of integrating passenger and freight transport in a single system, thus overcoming the tactical/operational dimension, often used in emergency situations but not part of long-term visions about the future of mobility. It will deliver the enablers – both on technical and governance/regulatory level, towards a federated network of platforms for green, multimodal passenger and freight transport, capable of sharing in a seamless and secure manner, cross-sectoral, multi-modal passenger and freight transport data, as well as on traffic management systems information, as if those were part of a single system.

In particular, DELPHI will deliver architectural enablers towards secure data federation (interfaces, security mechanisms, etc.) in a Data Spaces-driven approach, novel governance and regulatory schemes (stakeholder and ecosystem specifications, information flows, data sovereignty principles, regulatory artefacts), novel and ultra-efficient methodologies for traffic monitoring such as Unmanned Aerial System-powered monitoring, multi-/inter-modal optimisation, Artificial Intelligence (AI) /Machine Learning (ML) – powered optimisations and frameworks, and will exploit diverse modes for hybrid passenger and freight transport (e-bike-powered crowd-shipping, subway, shuttle and taxi service) in different ecosystem types (urban, sub-urban, rural/island).