Bus arrival time prediction at bus stop with multiple routes

Bin Yu, Hing Keung William Lam, Mei Lam Tam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

217 Citations (Scopus)

Abstract

Provision of accurate bus arrival information is vital to passengers for reducing their anxieties and waiting times at bus stop. This paper proposes models to predict bus arrival times at the same bus stop but with different routes. In the proposed models, bus running times of multiple routes are used for predicting the bus arrival time of each of these bus routes. Several methods, which include support vector machine (SVM), artificial neural network (ANN), k nearest neighbours algorithm (k-NN) and linear regression (LR), are adopted for the bus arrival time prediction. Observation surveys are conducted to collect bus running and arrival time data for validation of the proposed models. The results show that the proposed models are more accurate than the models based on the bus running times of single route. Moreover, it is found that the SVM model performs the best among the four proposed models for predicting the bus arrival times at bus stop with multiple routes.
Original languageEnglish
Pages (from-to)1157-1170
Number of pages14
JournalTransportation Research Part C: Emerging Technologies
Volume19
Issue number6
DOIs
Publication statusPublished - 1 Jan 2011

Keywords

  • Artificial neural network
  • Bus arrival time prediction
  • K nearest neighbours algorithm
  • Multiple bus routes
  • Support vector machine

ASJC Scopus subject areas

  • Automotive Engineering
  • Transportation
  • Computer Science Applications
  • Management Science and Operations Research

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