Detection of Statistically Significant Bus Delay Aggregation by Spatial-Temporal Scanning

摘要：

　　Public bus service plays an indispensable role in modern urban traffic system.With the bus running data,the detection of the statistically significant aggregations of bus delay is useful for optimizing the bus timetable,so that the service quality can be improved.However,previous studies have not considered how to detect bus delay aggregation using statistical hypothesis testing.To fill that gap,this paper considers the detection of bus delay aggregation from bus running data.We present RSTV-Miner,a mining method using statistical hypothesis testing,for detecting statistically significant bus delay aggregation.Our empirical study on real data demonstrates that RSTV-Miner is effective and efficient.

关键词： Bus delay aggregation Spatial-temporal analysis Traffic data mining

作者: Xia Wu Lei Duan Tinghai Pang Jyrki Nummenmaa

作者单位: School of Computer Science,Sichuan University,Chengdu,China School of Computer Science,Sichuan University,Chengdu,China;West China School of Public Health,Sichu School of Information Sciences,University of Tampere,Tampere,Finland;Sino-Finnish Centre,Tongji Univ

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 277-288

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）