Finding a sustainable mobility solution for the future is one of the most competitive challenges in the logistics and mobility sector. As a result, policymakers, researchers, and companies are working intensively to provide novel, environmentally friendly, and sustainable options.
While autonomous car-sharing services have been introduced as a promising solution, an innovative alternative is the use of self-driving bikes. Shared autonomous cargo-bike fleets are likely to increase the livability and sustainability of the city, as the use of cargo bikes in an on-demand mobility service can replace the use of cars for short-distance trips and enhance connectivity to public transportation. However, more research is needed to develop this new concept.
In a paper, researchers from the Institute of Logistics and Material Handling Systems, Otto von Guericke University Magdeburg, investigate different rebalancing strategies for an on-demand, shared-use, self-driving cargo-bikes service (OSABS). In addition, the research investigates fleet management strategies to find the best balance between customer satisfaction and cost reduction for OSABS. On the one hand, customers want quick and reliable access to bikes, resulting in a large fleet and frequent rebalancing. On the other hand, fleet operators are interested in the economic viability of their service. Consequently, they aim to reduce energy (mainly from idle traveling) and fleet costs as much as possible. Finding a favorable balance for both parties allows for the sustainable use of the service.
They simulate a case study of the system in the inner city of Magdeburg using AnyLogic. The simulation model allows us to evaluate the impact of rebalancing on service level, idle mileage, and energy consumption. They conclude that their case study’s best proactive rebalancing strategy is to relocate bikes only between neighboring regions. However, they also acknowledge the importance of bike relocation to improve service efficiency and reduce fleet size.
Source: Haj Salah, I., Mukku, V. D., Kania, M., Assmann, T., & Zadek, H. (2022). Implications of the Relocation Type and Frequency for Shared Autonomous Bike Service: Comparison between the Inner and Complete City Scenarios for Magdeburg as a Case Study. Sustainability, 14(10), 5798.