AI-based simulation model for optimal placement of micro-hubs and cargo bike pick-up stations

This document explains the findings from Task 2.3 with the aim to create an AI-based simulation model for the optimal placement of micro-hubs and cargo bike pick-up stations as a case study in the city of Leipzig, Germany. The objective of this task is to use available open data (see data catalogue from Deliverable 2.2) to develop this model and simulate the best possible location for micro-hubs and stationary cargo bike pick-up stations. Regarding the challenges delineated in Deliverable 2.1 Review of challenges for sustainable goods logistics and delivery solutions in urban outskirts, the proposed locations consider inclusivity, barrier-free and social aspects. Although the simulation model is trained primarily from data from Leipzig, it would still be able to be extended for use in municipalities outside of these geographic areas. Additionally, in Task 2.4, a software prototype for bike couriers for delivery scheduling and routing is developed and can be used as a supplement to a holistic logistics concept for outskirts. The model will be further refined and developed during the pilot project phase. Further cities, such as Merano, Italy and Dresden, Germany, will be added to the model. It is worth noting that while Dresden isn’t a SuCoLo pilot city, it was chosen due to its excellent cycling infrastructure and comparability to Leipzig; thus, it is relevant to be used as a benchmark for comparison. This deliverable outlines the background and development of a simulation model that identifies optimal locations for pick-up stations for parcels, cargo bike rentals and micro-hubs in suburban or outskirt areas. These aforementioned stations are designed to improve the efficiency of last-mile logistics by integrating community aspects and delivery demands. The tool primarily targets urban delivery companies, promoting not only operational efficiency, but also the context-specific needs of outskirt residents. The simulation model takes the form as an app and is based on findings from a citizen survey in the Lützschena-Stahmeln district in Leipzig, Germany conducted in 2025. Resulting from this, three personas and user stories channeled the real-world requirements to the model. Interim results demonstrate that further refinement of the model is necessitated, and further iterative developments will be included in D4.3 Reports on the research pilots’ design, implementation and results. In the end, the simulation model will be able to be found open access under the following link: https://github.com/Logistics-Living-Lab .