Demand-responsive transit (DRT) is a flexible alternative to traditional, fixed-route mass-transit networks. Although DRT can function well in low-density communities, high operating costs and low reliability are common issues. We propose that these issues can be mitigated by moving from a centralized, manually-scheduled scheme to a distributed system capable of dynamically routing multiple vehicles using a slime-mold-inspired routing algorithm to maximize network effectiveness. We additionally introduce the method of dynamic transfers to further optimize transit network efficiency. All passenger allocation and dynamic transfers are handled via a continual cooperative bidding process by the buses. In this paper, we present simulated results for a swarm-driven transit network in suburban, urban, and semi-rural scenarios, using map networks pulled from OpenStreetMap. We show that our approach increases passenger delivery rates relative to a fixed-network approach by 28%, 49%, and 101%, respectively, and results in over 75% reduction in walking time in all cases.

翻译：需求响应式公交（DRT）是传统固定线路公共交通网络的一种灵活替代方案。尽管DRT在低密度社区表现良好，但高运营成本和低可靠性是常见问题。我们提出，通过从集中式人工调度模式转向分布式系统——该系统采用基于黏菌启发的路由算法动态调度多辆车以最大化网络效能——可缓解上述问题。我们还引入动态换乘方法以进一步优化公交网络效率。所有乘客分配与动态换乘均通过公交车之间的持续协作竞价过程实现。本文基于OpenStreetMap提取的地图网络，呈现了城市、郊区和半乡村场景下群智驱动公交网络的仿真结果。结果表明，相较于固定线路网络，我们的方法分别使乘客送达率提升28%、49%和101%，且在全部场景中步行时间减少超75%。