Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration. The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).

Large-scale social digital twinning projects are complex with multiple objectives. For example, a social digital twinning platform for innovative last-mile delivery solutions may aim to assess consumer delivery method choices within their social environment. However, no single tool can achieve all objectives. Different simulators exist for consumer behavior and freight transport. Therefore, we propose a high-level architecture and present a blueprint for a generic modelling framework. This includes defining modules, input/output data, and interconnections, while addressing data suitability and compatibility risks. We demonstrate the framework’s effectiveness with two real-world case studies.

We present a simulation tool for evaluating team formation in autonomous multi-UAV (Unmanned Aerial Vehicle) missions that operate Beyond Visual Line of Sight (BVLOS). The tool models UAV collaboration and mission execution in dynamic and adversarial conditions, where Byzantine UAVs attempt to disrupt operations. Our tool allows researchers to integrate and compare various team formation strategies in a controlled environment with configurable mission parameters and adversarial behaviors. The log of each simulation run is stored in a structured way along with performance metrics so that statistical analysis could be done straightforwardly. The tool is versatile for testing and improving UAV coordination strategies in real-world applications.

The vast range of possible fully autonomous multiunmanned aerial vehicle (multi-UAV) operations is creating a new and expanding market where technological advances are happening at a breakneck pace. The integration of UAVs in airspaces (not just for military purposes but also for civil, commercial, and leisure use) is essential in realizing the potential of this growing industry. Furthermore, with the advent of 6G, such integration will be cost-effective and more flexible. However, to reach widespread adoption, new models focusing on the safety, efficiency, reliability, and privacy of fully autonomous multi-UAV operations, ensuring that the operation history is trustworthy and can be audited by the relevant stakeholders, need to be developed. Accordingly, this work presents a research guideline for fully autonomous trustworthy UAV teamwork through layer 2 blockchains that provide efficient, privacy-preserving, reliable, and secure multi-UAV service delivery. We show the implications of this approach for an aerial surveillance use case.