基于大数据的共享单车出行需求分析方法和应用——以上海为例

Travel Demand Analysis of Bike-Sharing Based on Big Data:Taking Shanghai as an Example

共享单车由粗放竞争迈向有序发展过程中,精准把握其出行需求特征是至关重要的基础,共享单车庞大的数量、复杂多样的出行特征长期以来也是其运营和管理上的难点。该文基于GIS空间数据、共享单车实际运营和手机信令等多源数据,以上海市为例,对共享单车的出行特征、热点和需求进行了分析,提出了基于点、线、核的密度计算和分区分析方法。同时,针对共享单车出行强度高的典型地区,以中山公园—漕河泾开发区区域为例,创新出一种针对共享单车的运营-规划-政策的闭环反馈工作方法,将区域人口、岗位及交通供给与共享单车出行需求进行关联,为共享单车额度控制、非机动车停放设施布局和企业运营监管等提供可视化、定量化的依据。在此基础上,提出对共享单车运营管理层面的建议,以期更好地引导共享单车行业规范发展,为有需求的市民提供便捷有序的出行服务。

From inefficient competition to orderly development,precisely grasping the travel demand characteristics are the basis for bike-sharing,which also cause the difficulties for operation and management.Based on the GIS,operation and cellular signaling data,this paper,taking Shanghai as an example,points out the density calculation method(based on point,line and core)and zoning analysis to analyse travel characteristics and demand.Aiming at the typical areas with high intensity of shared-bicycle travel,this paper attempts to explore a closed-loop feedback method for the operation-planning-policy of bike-sharing,by building a correlation between population,position,traffic supply and travel demand of shared-bicycle,so as to optimize the operation and supervision strategy and to provide convenient and orderly services for citizens with demand.