Robots and Vans: A Smarter Mix for the Last Mile

Autonomous delivery robots are no longer science fiction. They’re becoming real players in last-mile logistics. Their appeal is clear: robots can cut costs, lower emissions, ease congestion, and even reach narrow streets where vans struggle. But robots come with limits too. Their range, carrying capacity, and need for regular maintenance mean they can’t replace vans entirely.

That’s where a hybrid approach comes in. Imagine vans and robots working together: vans take care of bulky items and longer routes, while robots handle lighter, short-distance deliveries. This mix could make last-mile logistics cleaner, cheaper, and more efficient.

A Swedish project, Helsingbotica, has been testing just that. With partners including VTI, Hugo, Apotea, BEST Transport, and the City of Helsingborg, the project explored the practical combination of vans and robots. Using detailed data on building density and road networks from OpenStreetMap, researchers simulated parcel demand and designed service zones. They then applied a mathematical model to assign parcels to robots or vans, based on factors such as weight, distance, and energy consumption. The goal was to allocate parcels to vans and robots to minimize delivery costs and energy use, while assessing collaborative robot-van setups across various configurations.

The results are promising. Depending on how the system is configured, costs could decrease by as much as 57%, while energy consumption could decrease by up to 42%. That’s a significant step toward more sustainable city logistics.

For logistics providers, the lesson is clear: robots won’t replace vans, but they can complement them. By building flexible, hybrid systems, companies can save money, cut emissions, and offer better service in crowded urban areas. Autonomous robots may be small, but in the broader context of sustainable logistics, they can make a significant difference.

Source: Klar, R., Arvidsson, N., & Rudmark, D. (2025). Towards a new last-mile delivery system: Cost and energy-optimized robot and van allocation. Transportation Research Part E: Logistics and Transportation Review, 204, 104392. https://doi.org/10.1016/j.tre.2025.104392

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