面向公交站点优化的多源数据可视分析方法

Visualization Analysis of Bus Stop Optimization Based on Multi-source Data

“公交+共享单车”模式已经成为城市出行的主要方式,公交站点设置的合理与否直接影响公交服务水平,如何评估站点设置的合理性及如何优化,成为城市规划的研究热点.共享单车产生的GPS数据可以反映人口分布、出行模式、城市热点等规律.基于上述背景,本文探索了一种通过共享单车、城市兴趣点等多源数据,帮助交通规划人员理解站点周围环境并对站点进行优化的解决思路,设计了一种可缩放的蜂窝状视图来显示兴趣点的空间分布,设计了一种径向布局的分层雷达图来分析人流的时间序列信息,提出了基于多源数据集的公交站点优化可视分析模型,并在此基础上设计实现了一个可视分析系统VisB4B.该系统以上海市公交线路站点数据、城市兴趣点数据、摩拜共享单车数据等为数据源,通过公交线路变化实例评估、交通可视化领域和交通规划领域专家评估等方法,验证了系统的有效性与可用性.

The mode of"bus+sharing bikes"has become the primary mode of urban travel.Whether the setting of a bus stop is reasonable or not directly affects the level of public transport service.How to evaluate the rationality of the station setting and how to optimize it has become the research focus of urban planning.The GPS data generated by sharing bikes can reflect the rules of population distribution,travel patterns,urban hotspots,and so on.Based on the above background,this paper explores a solution to help traffic planners understand the environment around the bus stop and optimize it by sharing bikes,urban POI,and other multi-source data.The paper also designs a scalable honeycomb view to display the spatial distribution of POI,and designs a hierarchical radar map with the radial layout to analyze the time-series information of human flow.In this paper,a visual analysis model of bus stop optimization based on multi-source data sets is proposed,and a visual analysis system VisB4B is designed and implemented.The system uses Shanghai bus line station data,POI data,and Mobike sharing bike data as data sources,and verifies the effectiveness and availability of the system through examples of bus route changes,and expert evaluation from the field of traffic visualization and traffic planning.