Optimizing Deliveries in Urban Areas Through the Implementation of Autonomous Delivery Vehicles or Cargo Bikes: A Comparison

The growing global population, coupled with a rapid increase in urbanization, poses major challenges for urban logistics. By 2050, 66% of the world’s popula-tion is expected to live in urban areas, intensifying the demand for efficient and sustainable delivery solutions. Simultaneously, the rise of e-commerce and the pressing need to reduce the environmental impact of logistics operations call for innovative last-mile delivery approaches. This study investigates the optimization of last-mile delivery operations in urban context through the adoption of autono-mous delivery vehicles (ADVs) and cargo bikes (CB), assessing their efficiency through performance indicators, such as energy consumption, delivery times, and distance travelled. A test case is implemented to determine optimal delivery tours for both ADVs and CBs. To better reflect real-world conditions, the Multi-Trip Vehicle Routing Problem (MTVRP) is addressed, allowing vehicles to return to the depot and complete multiple trips within a specified time frame, ensuring a re-alistic evaluation of the effects of operational constraints. The comparative analysis highlights clear trade-offs between the two delivery methods: CBs demonstrate advantages in energy efficiency and faster delivery times, aided by the operator’s ability to unload quickly upon arrival, while ADVs offer greater scalability and reduced workforce dependency, making them a viable option for high-density urban areas or regions with limited workforce availability. The findings provide practical insights for urban logistics stakeholders, showing how ADVs and CBs can contribute to more sustainable and effective last-mile delivery systems, aligned with the needs of evolving urban environment.