A hybrid scheme for real-time prediction of bus trajectories

Masoud Fadaei, Oded Cats, Ashish Bhaskar

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

The uncertainty associated with public transport services can be partially counteracted by developing real-time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real-time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances.

Original languageEnglish
Pages (from-to)2130-2149
Number of pages20
JournalJournal of Advanced Transportation
Volume50
Issue number8
DOIs
Publication statusPublished - 2016

Keywords

  • bus reliability
  • hybrid model
  • linear regression heuristic
  • real-time information
  • travel time prediction
  • vehicle trajectory

Fingerprint Dive into the research topics of 'A hybrid scheme for real-time prediction of bus trajectories'. Together they form a unique fingerprint.

Cite this