Journal of Transportation Systems Engineering and Information Technology ›› 2019, Vol. 19 ›› Issue (1): 76-82.

• Intelligent Transportation System and Information Technology • Previous Articles     Next Articles

Public Transportation Travel Multi-dimensional Analysis Method Based on APTS Big Data

CHEN Jun1, ZHUANG Yi-fei1, CUI Mei-li1, WANG Yin-hai2, MA Dong-fang3   

  1. 1. School of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China; 2. School of Civil and Environment Engineering, University of Washington, Seattle 98195, USA; 3. Ocean College, Zhejiang University, Hangzhou 310058, China
  • Received:2018-09-17 Revised:2018-11-23 Online:2019-02-25 Published:2019-02-25

基于APTS大数据的城市公交出行多维分析模型和方法

陈君*1,庄义斐 1,崔美莉 1,王印海 2,马东方 3   

  1. 1. 西安建筑科技大学 土木工程学院,西安 710055;2. 华盛顿大学 土木环境工程系,西雅图 98195, 美国; 3. 浙江大学 海洋学院,杭州 310058
  • 作者简介:陈君(1977-),男,陕西平利人,副教授.
  • 基金资助:

    国家自然科学基金/ National Natural Science Foundation of China(51208408);陕西省自然科学基础研究计划项目/ National Natural Science Foundation of Shaanxi Province of China(2017JM5121);教育部人文社会科学研究项目/ Humanity and Social Science Foundation of Ministry of Education of China(17YJCZH124).

Abstract:

Advanced Public Transportation Systems (APTS) data have the typical characteristics of massive and diverse data. It is possible to obtain abundant transit travel characteristics and rules by analyzing and mining APTS data. The multi-dimensional analysis framework of bus travel based on APTS data is constructed. On the basis of calculating passenger travel time-space information (boarding, alighting and transferring), the multi-dimensional data model of transit travel with four dimensions (passenger, time, space and behavior) is established. Then, the content of public transportation travel multi- dimension analysis based on 5 kind of online analysis process operations is systematically presented. Finally, the model and the method are experimented and verified using APTS big data. The results show that this method can easily analyze different dimensions and granularities of transit travel information and can not only be applied to the study of transit travel behavior, but also provides decision-making support for the planning and management of urban public transportation system.

Key words: intelligent transportation, public transportation travel, multi-dimensional data model, online analysis process, visualization analysis

摘要:

智能公交系统(Advanced Public Transportation Systems,APTS)数据具有海量、类型多样等大数据的典型特征,对其进行分析和挖掘可能获得丰富的公交出行特征和规律.构建基于APTS大数据的公交出行多维分析框架,在计算乘客出行时空信息(上车、下车和换乘)的基础上,建立包含4个维度(乘客、时间、空间和行为)的公交出行数据模型,系统提出基于5种联机分析处理方法的公交出行分析内容.应用APTS大数据对模型和方法进行了实验和验证,研究结果表明,该方法能够便捷地分析不同维度、不同粒度的公交出行信息,不仅能够应用于公交乘客出行行为的研究,还能够为城市公交系统的规划和管理提供决策支持.

关键词: 智能交通, 公交出行, 多维数据模型, 联机分析处理, 可视化分析

CLC Number: