Pilot action
Smart Redistribution for Suburban Bike-Sharing in Northern Saxony
PA core objective: to increase usage of shared bikes in free-floating systems, specifically in less densely populated peri-urban areas to support the broader regional aim of promoting economically viable intermodal mobility solutions. This requires both higher usage rates and a reduction in human resource dependency, particularly for the costly manual redistribution of bikes. This PA will run in Schkeuditz, Germany, inspired by initiatives as BORA! in PT and BikeMet in IT, tackling a common challenge in suburban bike-sharing: the imbalance between bike drop-off locations and high-demand areas, e.g., train stations.
PA will simulate a bike redistribution system over approx. 150 days. Before autonomous robotic redistribution can be deployed, real-world dynamics of bike usage and movement in the area must be understood. PA addresses this by simulating robotic redistribution: human participants will manually redistribute bikes for 1–4 hours daily while carrying sensory backpacks equipped with GPS, obstacle detection sensors, and environmental data loggers. They act as stand-ins for autonomous robots, allowing us to gather high-resolution empirical data on feasible routes, physical barriers, route efficiency, pick-up/drop-off hotspots, and usage peaks. The backpacks are crucial for collecting data on movement patterns, identifying key zones of imbalance, and evaluating the efficiency of redistribution routes, serving as a prototype for a future robotic solution planned by the District Administration for 2026–2027. A research institute/university will be contracted to manage the backpack technology, gather and evaluate data, and support iterative improvements to the sensory setup. Data will be supplemented by anonymised usage data from a local bike-sharing provider, comprehensively tracking redistribution performance. Through this PA, the region can assess both short-term improvements and feasibility of scaling to autonomous redistribution solutions in low-density areas.
PA will simulate a bike redistribution system over approx. 150 days. Before autonomous robotic redistribution can be deployed, real-world dynamics of bike usage and movement in the area must be understood. PA addresses this by simulating robotic redistribution: human participants will manually redistribute bikes for 1–4 hours daily while carrying sensory backpacks equipped with GPS, obstacle detection sensors, and environmental data loggers. They act as stand-ins for autonomous robots, allowing us to gather high-resolution empirical data on feasible routes, physical barriers, route efficiency, pick-up/drop-off hotspots, and usage peaks. The backpacks are crucial for collecting data on movement patterns, identifying key zones of imbalance, and evaluating the efficiency of redistribution routes, serving as a prototype for a future robotic solution planned by the District Administration for 2026–2027. A research institute/university will be contracted to manage the backpack technology, gather and evaluate data, and support iterative improvements to the sensory setup. Data will be supplemented by anonymised usage data from a local bike-sharing provider, comprehensively tracking redistribution performance. Through this PA, the region can assess both short-term improvements and feasibility of scaling to autonomous redistribution solutions in low-density areas.
Addressed policy instruments
Leipzig - City for Intelligent MobilityPartners
Aufbauwerk Region Leipzig GmbH
Germany
Leipzig