Reliability prediction of further transit service based on support vector machine

  • Xiaoning Gu
  • , Chao Chen
  • , Yunong Yang
  • , Xingzhi Miao
  • , Baozhen Yao (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
46 Downloads (Pure)

Abstract

The requirement for transit reliability grows with the increase of pace of life since unstable bus arrivals can raise the anxiety of waiting passengers. This paper proposes a reliability assessment method to evaluate the reliability of each bus stop on the route and the reliability of bus routes. In reliability prediction, the prediction target is locked by rolling horizon to reduce the interference of other information. In addition, a prediction method of the reliability of further transit service using the accurate online support vector machine is proposed. This prediction can provide more accurate and stable data for the arrival of buses and reduce unnecessary waiting of passengers. Finally, the reliability prediction method proposed is tested with the real data of a bus route in Dalian, China. The results show that the accurate online support vector machine with reasonable parameters can predict the reliability of transit service accurately.
Original languageEnglish
Pages (from-to)845-855
Number of pages11
JournalMeasurement and Control
Volume54
Issue number5-6
Early online date26 May 2020
DOIs
Publication statusPublished - May 2021

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by National Natural Science Foundation of China 51578112 and The State Key Laboratory of Structural Analysis for Industrial Equipment S18307.

Keywords

  • public transport
  • Reliability prediction
  • support vector machine

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