DSpace
 

iRepository at Perpustakaan UniMAP >
Professional Associations >
IEM Journal >

Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/13714

Title: ARIMA models for bus travel time prediction
Authors: Suwardo
Madzlan, Napiah
Ibrahim, Kamaruddin
???metadata.dc.contributor.url???: suwardo@yahoo.com
Keywords: Autoregressive Integrated Moving Average;Bus travel time;Mean absolute percentage prediction error;Mean absolute relative error;Time series model
Issue Date: Jun-2010
Publisher: The Institution of Engineers, Malaysia
Citation: The Journal of the Institution of Engineers, Malaysia, vol. 71(2), 2010, pages 49-58
Abstract: In this paper, the time series model, Autoregressive Integrated Moving Average (ARIMA) is used to predict bus travel time. ARIMA model is simpler used for predicting bus travel time based on travel time series data (historic data) compared to regression method as the factors affecting bus travel time are not available in detail such as delay at link, bus stop, intersection, etc. Bus travel time prediction is an important aspect to bus operator in providing timetable for bus operation management and user information. The study aims at finding appropriate time series model for predicting bus travel time by evaluating the minimum of mean absolute relative error (MARE) and mean absolute percentage prediction error (MAPPE). In this case, data set was collected from the bus service operated on a divided 4-lane 2-way highway in Ipoh-Lumut corridor, Perak, Malaysia. The estimated parameters, appropriate model, and measures of model performance evaluation are presented. The analysis of both Ipoh to Lumut and Lumut to Ipoh directions is separately performed. The results show that the predicted travel times by using the moving average, MA(2) and MA(1) model, clearly fit with the observed values for both directions, respectively. These appropriate models are indicated by the minimum MARE and MAPPE values among the tentative models. It is concluded that MA(2) and MA(1) models are able to be appropriately applied in this case, and those models can be used for bus travel time prediction which helping in the timetable design or setup.
Description: Link to publisher's homepage at http://www.myiem.org.my/
URI: http://www.myiem.org.my/content/iem_journal_2010-181.aspx
http://hdl.handle.net/123456789/13714
ISSN: 0126-513X
Appears in Collections:IEM Journal

Files in This Item:

File Description SizeFormat
049-058Arima Models For Bus Travel 3pp.pdf1.28 MBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Perpustakaan Tuanku syed Faizuddin Putra, Kampus Pauh Putra, Universiti Malaysia Perlis, 02600, Arau Perlis
TEL: +604-9885420 | FAX: +604-9885405 | EMAIL: rujukan@unimap.edu.my Feedback