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.
Improved iterative prediction for multiple stop arrival time using a support vector machine
2012
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Bus arrival time prediction at bus stop with multiple routes
Elsevier | 2011
|Bus arrival time prediction at bus stop with multiple routes
Online Contents | 2011
|Bus arrival time prediction using mixed multi-route arrival time data at previous stop
DOAJ | 2018
|Bus arrival time prediction method through optimizing support vector machine based on bat algorithm
European Patent Office | 2016
|