Urban logistics is under mounting pressure. Population density is rising, e-commerce is accelerating, and regulatory requirements are tightening. Traditional logistics systems, with their reliance on static planning, are increasingly inadequate. They struggle to adapt to the dynamic realities of urban environments, leading to inefficiencies, congestion, and environmental challenges. A recent paper by Liu, Pan, and Ballot (2025) explores how federated digital twin platforms can transform city logistics by enabling real-time visibility, knowledge-driven decision-making, and cross-stakeholder collaboration.
The authors propose a federated digital twin framework that synchronizes physical logistics assets—such as parking spaces, micro-hubs, and delivery vehicles—with their virtual representations. This allows logistics service providers (LSPs), city planners, and policymakers to monitor system performance and adapt operations dynamically and continuously. Unlike traditional static models, this framework integrates knowledge of delivery destinations, urban regulations, and preferred logistics modalities, ensuring operations remain context-sensitive and responsive to real-time changes.
Methodologically, the study uses an optimization-based simulation framework to test multi-echelon logistics networks, combining micro-hubs, dynamic transshipment points, and multimodal options such as on-foot couriers, e-cargo bikes, and road autonomous delivery robots (RADRs). The findings are striking. Knowledge-driven modality selection and clustering reduce logistics costs by more than 50 percent and emissions by over 30 percent compared to baseline scenarios. These results demonstrate the value of embedding delivery knowledge into logistics operations rather than relying solely on technical optimization.
For practitioners, the paper provides several actionable insights. First, modal shift strategies, particularly those toward e-cargo bikes, are cost-effective and significantly reduce emissions. However, the benefits depend on micro-hub accessibility, which requires careful planning and alignment with local land-use policies. Second, while RADRs offer scalable and potentially cost-efficient alternatives, operators must weigh long-term feasibility, regulatory compliance, and infrastructure readiness before large-scale deployment. Third, federated digital twins provide the foundation for knowledge-driven logistics, strengthening collaboration between LSPs and municipalities. This approach facilitates the shared use of infrastructure, supports compliance with regulations for low- and zero-emission zones, and enhances regulatory alignment.
From a policy perspective, the study highlights the importance of adaptive regulatory frameworks. Cities should integrate logistics performance into urban planning, adopt dynamic curb and access management, and consider incentive structures that reward sustainable practices. The federated digital twin model aligns well with the Physical Internet vision of open, interconnected logistics systems. By promoting interoperability and shared resource use, it provides a pathway to strengthen supply chain resilience and reduce environmental impacts.
There are, however, challenges. Implementing such platforms requires significant investment in sensing infrastructure, data-sharing agreements that respect privacy, and stakeholder engagement to overcome resistance from operators. The study’s focus on quasi-actual data from a single proof-of-concept application limits its generalizability. Broader validation across multiple cities and scenarios, including integration of electric and autonomous vehicle fleets, is needed.
Despite these limitations, Liu, Pan, and Ballot make an essential contribution to the smart city logistics literature. Their work illustrates how federated digital twins can move urban freight planning from reactive interventions to predictive, adaptive strategies. By emphasizing knowledge-driven operations, the study provides a clear vision for how cities and logistics providers can collaborate to strike a balance between efficiency, sustainability, and liveability.
Reference: Liu, Y., Pan, S., & Ballot, E. (2025). Federated digital twins platform for smart city logistics: A knowledge-driven approach. International Journal of Production Economics, 109772. https://doi.org/10.1016/j.ijpe.2025.109772