An Adaptive Algorithm for Public Transport Arrival Time Prediction Based on Hierarchical Regression

In this paper the authors consider a problem of public transport arrival time prediction for a large city in real time. The authors propose a new prediction algorithm based on a model of an adaptive combination of elementary prediction algorithms, each of which is characterized by a small number of adjustable parameters. Adaptability means that parameters of the constructed combination depend on a number of control parameters of the model, which includes the following factors: weather conditions, traffic density, driving dynamics, prediction horizon, and others. Adaptability is achieved by the use of a hierarchical regression (similar to a regression tree). The proposed arrival prediction algorithm has been tested with the data of all the public transport routes in Samara, Russia.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: 2776-2781
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01615721
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:16PM