Estimating destination of bus trips considering trip type characteristics

Soongbong Lee, Jongwoo Lee, Bumjoon Bae, Daisik Nam, Seunghoon Cheon

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or policy decision support due to missing information on alighting stops of users. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. In order to overcome these limitations, various methods for estimating alighting stops have been developed. This study classifies trips with missing alighting stop information into trip four types and then applies appropriate alighting stop estimation methodology for each trip type in stages. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checking the accuracy for each standard of allowable error for sensitivity analysis. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can estimate users’ destinations more accurately than the methodologies of previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies.

Original languageEnglish
Article number10415
JournalApplied Sciences (Switzerland)
Volume11
Issue number21
DOIs
StatePublished - 1 Nov 2021

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Categorization of trip types
  • Estimation of destination
  • Historical travel data
  • Public transit transaction data
  • Travel pattern
  • Trip chain

Fingerprint

Dive into the research topics of 'Estimating destination of bus trips considering trip type characteristics'. Together they form a unique fingerprint.

Cite this