Sustainable Urban Logistics: How GNSS Data Inform Microhub Design for Greener Last-Mile Delivery

The rapid expansion of e-commerce has led to a sharp rise in urban parcel deliveries, placing growing pressure on city logistics systems. As freight activity intensifies in dense urban areas, the traditional model of door-to-door delivery becomes increasingly untenable due to failed delivery attempts, limited curb availability and infrastructural constraints typical of dense urban environments. In response, a broad spectrum of alternative strategies has emerged, with particular focus on last-mile optimization. Among these, microhubs, small decentralized logistics facilities located near the final delivery destination, have gained significant attention as a promising solution. This work proposes a data-driven methodology for identifying optimal locations for urban microhubs, based solely on GNSS data collected from commercial delivery vehicles. Building on the spatial distribution and duration of observed delivery stops, the approach combines clustering techniques with constrained optimization to minimize the distance between customers and microhubs. The underlying demand distribution is inferred from stop duration and spatial density, and is used to prioritize areas with higher delivery intensity in the placement process.The resulting microhub configurations are evaluated through simulation and show the potential to reduce pollutant emissions, travel distances and delivery times compared to the traditional door-to-door delivery model. The method offers a practical and effective solution to the challenges of last-mile delivery, and is both scalable and transferable to other urban contexts.