Urban Mobility Swarms: Towards a Decentralized Autonomous Bicycle-Sharing System.

Urban mobility can often be categorized as a complex system—e.g., a nonlinear system composed of many interacting components with interdependent relationships. The growing trend towards shared, lightweight, and autonomous vehicles requires planning solutions that are less centralized and can manage the increasing complexities of new mobility. This research investigates planning strategies for shared micro-mobility systems, focusing on shared autonomous bicycles. Vehicle rebalancing within such systems poses a critical technical challenge and has substantial environmental and economic implications. To tackle this challenge, we propose a fully decentralized approach that allows autonomous bicycles to rebalance in a self-organizing manner via stigmergy, a bio-inspired mechanism for indirect communication. While the bicycles autonomously navigate their urban environment, they locally update RFID tags at intersections, leaving virtual pheromone trails that collectively guide each other toward high-demand areas. The efficacy of our approach is assessed through a realistic agent-based model of Cambridge, MA (USA). Results highlight the capacity of autonomous bicycles to rebalance in a self-organized manner, using strictly decentralized local communication, while significantly reducing the average user wait time compared to no rebalancing and random rebalancing. These findings emphasize the feasibility and potential of decentralized planning strategies in handling complexity within new mobility systems.