Improved iterative prediction for multiple stop arrival time using a support vector machine

    Chang-Jiang Zheng Info
    Yi-Hua Zhang Info
    Xue-Jun Feng Info
DOI: https://doi.org/10.3846/16484142.2012.692710

Abstract

The paper presents an improved iterative prediction method for bus arrival time at multiple downstream stops. A multiple-stop prediction model includes two stages. At the first stage, an iterative prediction model is developed, which includes a single stop prediction model for arrival time at the immediate downstream stop and an average bus speed prediction model on further segments. The two prediction models are constructed with a support vector machine (SVM). At the second stage, a dynamic algorithm based on the Kalman filter is developed to enhance prediction accuracy. The proposed model is assessed with reference to data collected on transit route No 23 in Dalian city, China. The obtained results show that the improved iterative prediction model seems to be a powerful tool for predicting multiple stop arrival time.

First Published Online: 26 Jun 2012

Keywords:

multiple stop, arrival time, prediction, support vector machine, Kalman filter

How to Cite

Zheng, C.-J., Zhang, Y.-H., & Feng, X.-J. (2012). Improved iterative prediction for multiple stop arrival time using a support vector machine. Transport, 27(2), 158-164. https://doi.org/10.3846/16484142.2012.692710

Share

Published in Issue
June 30, 2012
Abstract Views
710

View article in other formats

CrossMark check

CrossMark logo

Published

2012-06-30

Issue

Section

Original Article

How to Cite

Zheng, C.-J., Zhang, Y.-H., & Feng, X.-J. (2012). Improved iterative prediction for multiple stop arrival time using a support vector machine. Transport, 27(2), 158-164. https://doi.org/10.3846/16484142.2012.692710

Share