Improved iterative prediction for multiple stop arrival time using a support vector machine
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. 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.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/16484142
-
Supplemental Notes:
- Abstract reprinted with permission from Taylor and Francis
-
Authors:
- Zheng, Chang-Jiang
- Zhang, Yi-Hua
- Feng, Xue-Jun
- Publication Date: 2012-6
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References;
- Pagination: pp 158-164
-
Serial:
- Transport
- Volume: 27
- Issue Number: 2
- Publisher: Vilnius Gediminas Technical University (VGTU) Press
- ISSN: 1648-4142
- EISSN: 1648-3480
- Serial URL: https://journals.vgtu.lt/index.php/Transport
-
Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Arrivals and departures; Bus stops; Bus transit; Iterative methods; Kalman filtering; Mathematical prediction
- Uncontrolled Terms: Support vector machines
- Geographic Terms: Dalian (China)
- Subject Areas: Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01376488
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 27 2012 10:06AM