基于共享单车大数据的城市型自行车绿道选线规划途径研究

城市型自行车绿道对于鼓励居民慢行出行，缓解城市交通拥堵具有非常重要的价值。从共享单车社会行为大数据和绿地空间利用潜力分析两方面内容入手，构建了一个基于实际使用需求和城区可建设空间的城市型自行车绿道选线规划途径，并以北京海淀区为例开展实证探索。选线规划途径主要包括：利用共享单车起点—终点数据,并运用熵值法建立评价指标体系进行绿地节点利用潜力分析，确定关键连接节点；通过共享单车轨迹数据得到自行车使用的道路热度，提取现状线性绿地廊道，生成自行车绿道连接的土地适宜性成本栅格；利用连接节点和成本栅格计算最低成本路径，划定绿道选线。该选线途径将随着城市大数据的进一步丰富和准确而得到完善，具有很好的未来应用前景。

Study on Urban Bicycle Greenway Planning Based on Big Data Analysis of Shared Bicycle

Urban bicycle greenways are of great value in encouraging residents to travel non-motor vehicles and alleviate urban traffic congestion. Based on the analysis of shared bicycle social behavior big data and green space utilization potential, this paper constructs an urban bicycle greenway route selection method based on actual use demand and urban constructable space, and conducts empirical exploration with Beijing Haidian District. The route selection planning method mainly includes: using the shared bicycle OD data, and using the entropy method to establish an evaluation index system to analyze the utilization potential of the green space node to determine the key connection nodes; by sharing the bicycle track data to get the heat degree of the shared bicycle using road, and the linear green space distribution is extracted by remote sensing visual interpretation to obtain the potential of the greenway corridor based on the greenway connection; the lowest cost path is calculated by using the connection nodes and the cost grid, and the greenway selection line is delineated. The route selection method will be improved with the further enrichment and accuracy of urban big data, and has a good future application prospect.