城市共享单车的动态调度策略

Dynamic scheduling strategy for bicycle-sharing in cities

为满足城市共享单车用户的用车需求,提高共享单车的使用效率,结合路况信息提出了一个两阶段的共享单车实时投放与调度框架:在离线建模阶段,基于历史的短程出租车轨迹数据聚类,使用区域提取技术(Regional Extraction Technique,RET)获取不同时段的城市热门用车区域、用车频次与行程结束后的热门停车区域及其停车频次;在线调度阶段,建立共享单车的实时调度优化模型(Real-time OptimizationModel,ROM),根据下一时段的热门用车区域,搜索当前时段内距离其较近的k近邻单车停车区域,并结合实时路况为调度车推荐前k条路况良好的行车线路.出租车轨迹数据集上的实验表明,所提的调度策略相较于传统的自行车调度策略具有较好的有效性.

To meet the soaring demand of share bike using and improve the service efficiency of bicycle-sharing,this paper proposes a two-stage shared bicycle real-time delivery and scheduling framework based on road condition information.At the offline modeling phase,clustering is implemented on the historical short-distance taxi trajectory data using RET(Regional Extraction Technique)algorithm,to obtain the popular regions of pick-up(or drop-off),and the frequencies of the pick-up(or drop-off)at different time periods.At the online scheduling phase,a dynamic scheduling optimization model(called ROM(Real-time Optimization Model))for bicycle-sharing is designed to obtain the popular pick-up regions in the next time period.Specifically,searching for the k-nearest neighbor bicycle drop-off regions within the current time period,and combining them with the real-time road conditions to recommend the top-k roads with convenient vehicular access for the bike dispatching car.Experiments on the taxi trajectory dataset show that the proposed method is more effective than the traditional bicycle scheduling strategies.