中文摘要：

公交车辆在高低峰等不同时段的运营时间差异较大,因此,只有对各时段的运营时间分别加以分析才能准确掌握运营时间规律,这对提高公交运营方案的准点率具有重要影响,是公交运营分析和优化调度等工作的不可或缺的重要基础.目前我国公交时段划分主要依据人工经验,简单且粗糙.本文基于大量GPS运营数据,创新性地将K-means聚类算法应用于运营时段划分,并结合公交样本数据特点,提出一种改进的K-means聚类算法,其中改进了传统的初始簇中心选择方法,并设计了利用三角形不等式减少不必要的距离计算和基于模糊聚类思想的簇中心更新算法.十堰市和海口市公交的案例分析表明,本文的K-means聚类方法可行,改进算法的计算效率更高,划分的时段与实际调研分析结果更加吻合.

英文摘要：

Bus running time normally varies significantly by different time period like peack and non-peak hours.Therefore,the running time should be measured for individual time period,which affects the on-time probability of schedules.Setting precise homogeneous running time （HRT） bands is essential for service reliability measurement and scheduling.In China,the HRT bands are manually set based on experiences,and the HRT bands generated lack accuracy.With GPS data,this paper uses the K-means clustering algorithm to divide HRT bands.Then,the K-means algorithm is improved and an enhanced HRT bands division method is developed.Several methods are also addressed：an enhanced cluster initialization method,a cluster center updating method based on triangle inequality,and fuzzy clustering method.The field study on Shiyan Bus and Haikou Bus demonstrates the feasibility of the clustering method.The generated HRT bands match well with real-world situations.