Abstract: The current public transportation priority strategy mainly focused on the optimization of network accessibility, which improved the convenience of residents’ travel by improving the density of regional line networks and stations, while lacked consideration of public transportation resource scheduling and mobility orientation. In order to make up for the above defects, the process of bus travel was firstly divided into three stages, including riding, transferring and waiting. And a set of index systems and calculation methods of regional public transport accessibility covering three stages was put forward. Secondly, Pearson correlation coefficient was used to describe the correlation patterns between accessibility index and mobility level, and K-means clustering algorithm was used to divide the correlation patterns, mining the differences between urban areas and key accessibility elements oriented by mobility improvement. Finally, a case study was conducted by the proposed algorithm by taking Hangzhou City as an example. The research results show that the high accessibility of public transport does not necessarily lead to the improvement of mobility level. To address this inconsistency, regional strategies for the development of public transportation networks have been proposed.

Key words: traffic engineering; public transportation; accessibility; mobility; cluster analysis

摘要： 公交优先战略主要偏重于网络可达性优化，通过提高区域线网密度和站点密度可提升居民出行的便利性，但缺少对公交资源调度及移动性导向考虑。为弥补上述缺陷，首先将公交出行过程分为乘坐、换乘、候车等3个阶段，提出了一种涵盖3个阶段的区域公共交通可达性指标体系及测算方法；使用Pearson相关系数描述可达性指标与移动性水平的关联模式，采用K-means聚类算法划分关联模式，挖掘城市区域差异性和以移动性提升为导向的关键可达性要素；并以杭州市为例对该算法进行了案例分析。研究结果表明：公共交通的高可达性并非会带来移动性水平的必然提升，针对这种非一致性提出了分区域的公交网络发展策略。

关键词: 交通工程；公共交通；可达性；移动性；聚类分析