Understanding Daily Travel Patterns of Subway Users – An Example from the Beijing Subway

  • Hainan Huang College of Transportation & Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, China
  • Jian Rong Key Lab of Traffic Engineering, Beijing University of Technology, Beijing, China
  • Pengfei Lin Key Lab of Traffic Engineering, Beijing University of Technology, Beijing, China
  • Jiancheng Weng Key Lab of Traffic Engineering, Beijing University of Technology, Beijing, China
Keywords: daily travel pattern, smart card data, station sequence, subway user, data mining

Abstract

The daily travel patterns (DTPs) present short-term and timely characteristics of the users’ travel behaviour, and they are helpful for subway planners to better understand the travel choices and regularity of subway users (SUs) in details. While several well-known subway travel patterns have been detected, such as commuting modes and shopping modes, specific features of many patterns are still confused or omitted. Now, based on the automatic fare collection (AFC) system, a data-mining procedure to recognize DTPs of all SUs has become possible and effective. In this study, DTPs are identified by the station sequences (SSs), which are modelled from smart card transaction data of the AFC system. The data-mining procedure is applied to a large weekly sample from the Beijing Subway to understand DTPs. The results show that more than 93% SUs of the Beijing Subway travel in 7 DTPs, which are remarkably stable in share and distribution. Different DTPs have their own unique characteristics in terms of time distribution, activity duration and repeatability, which provide a wealth of information to calibrate different types of users and characterize their travel patterns.

Author Biography

Hainan Huang, College of Transportation & Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, China

Ph.D.; Research Interests: Public Transportation Planning, Management and Optimization

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Published
2020-01-20
How to Cite
1.
Huang H, Rong J, Lin P, Weng J. Understanding Daily Travel Patterns of Subway Users – An Example from the Beijing Subway. PROMET [Internet]. 2020Jan.20 [cited 2020Oct.20];32(1):13-. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/3052
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Articles