Modeling bus travel time reliability with supply and demand data from automatic vehicle location and smart card systems

Ma, Zhen-Liang, Ferreira, Luis, Mesbah, Mahnnoud and Hojati, Ahmad Tavassoli (2015) Modeling bus travel time reliability with supply and demand data from automatic vehicle location and smart card systems. Transportation Research Record, 2533 2533: 17-27. doi:10.3141/2533-03


Author Ma, Zhen-Liang
Ferreira, Luis
Mesbah, Mahnnoud
Hojati, Ahmad Tavassoli
Title Modeling bus travel time reliability with supply and demand data from automatic vehicle location and smart card systems
Journal name Transportation Research Record   Check publisher's open access policy
ISSN 0361-1981
2169-4052
Publication date 2015-01-01
Year available 2015
Sub-type Article (original research)
DOI 10.3141/2533-03
Open Access Status Not Open Access
Volume 2533
Issue 2533
Start page 17
End page 27
Total pages 11
Place of publication Washington, DC United States
Publisher U.S. National Research Council * Transportation Research Board
Language eng
Abstract Travel time reliability is an important aspect of bus service quality. Despite a significant body of research on private vehicle reliability, little attention has been paid to bus travel time reliability at the stop-to-stop link level on different types of roads. This study aims to identify and quantify the underlying determinants of bus travel time reliability on links of different road types with the use of supply and demand data from automatic vehicle location and smart card systems collected in Brisbane, Australia. Three general bus-related models were developed with respect to the main concerns of travelers and planners: average travel time, buffer time, and coefficient of variation of travel time. Five groups of alternative models were developed to account for variations caused by different road types, including arterial road, motorway, busway, and central business district. Seemingly unrelated regression equations estimation were applied to account for cross-equation correlations across regression models in each group. Three main categories of unreliability contributory factors were identified and tested in this study, namely, planning, operational, and environmental. Model results provided insights into these factors that affect bus travel time and its variability. The most important predictors were found to be the recurrent congestion index, traffic signals, and passenger demand at stops. Results could be used to target specific strategies aimed at reducing unreliability on different types of roads.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
Official 2016 Collection
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 2 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 07 Feb 2016, 10:26:13 EST by System User on behalf of School of Civil Engineering