Predicting arrival times of buses using real-time GPS measurements

Mathieu Sinn, Ji Won Yoon, Francesco Calabrese, Eric Bouillet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Citations (Scopus)

Abstract

Predicting arrival times of buses is a key challenge in the context of building intelligent public transportation systems. In this paper, we describe an efficient non-parametric algorithm which provides highly accurate predictions based on real-time GPS measurements. The key idea is to use a Kernel Regression model to represent the dependencies between position updates and the arrival times at bus stops. The performance of the proposed algorithm is evaluated on real data from the public bus transportation system in Dublin, Ireland. For a time horizon of 50 minutes, the prediction error of the algorithm is less than 10 percent on average. It clearly outperforms parametric methods which use a Linear Regression model, predictions based on the K-Nearest Neighbor algorithm, and a system which computes predictions of arrival times based on the current delay of buses. A study investigating the selection of interpolation points to reduce the size of the training set concludes the paper.

Original languageEnglish
Title of host publicationIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Pages1227-1232
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 21
Externally publishedYes
Event2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012 - Anchorage, AK, United States
Duration: 2012 Sep 162012 Sep 19

Other

Other2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
CountryUnited States
CityAnchorage, AK
Period12/9/1612/9/19

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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  • Cite this

    Sinn, M., Yoon, J. W., Calabrese, F., & Bouillet, E. (2012). Predicting arrival times of buses using real-time GPS measurements. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 1227-1232). [6338767] https://doi.org/10.1109/ITSC.2012.6338767