Effect of Automatic Vehicle Location on Schedule Adherence for Mass Transit Administration Bus System

2001 ◽  
Vol 1760 (1) ◽  
pp. 81-90 ◽  
Author(s):  
Young-Jae Lee ◽  
Kyung Soo Chon ◽  
David L. Hill ◽  
Nimish Desai
Keyword(s):  
Mass Transit ◽  
Automatic Vehicle Location ◽  
Vehicle Location ◽  
Schedule Adherence ◽  
Bus System

Modeling Bus Travel Time Reliability with Supply and Demand Data from Automatic Vehicle Location and Smart Card Systems

2015 ◽  
Vol 2533 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Zhen-Liang Ma ◽  
Luis Ferreira ◽  
Mahmoud Mesbah ◽  
Ahmad Tavassoli Hojati
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Supply And Demand ◽  
Seemingly Unrelated Regression ◽  
Regression Equations ◽  
Travel Time Reliability ◽  
Automatic Vehicle Location ◽  
Different Types ◽  
Vehicle Location ◽  
Bus Travel Time

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.

The Development of Datatrak

1991 ◽  
Vol 44 (1) ◽  
pp. 37-47 ◽  
Author(s):  
A. G. Scorer
Keyword(s):  
Great Britain ◽  
Reporting System ◽  
Automatic Vehicle Location ◽  
The Road ◽  
Vehicle Location ◽  
Road System

What are we doing it for? Datatrak designed, built and prepared for the transport market, a complete Automatic Vehicle Location and Reporting System (AVLRS) that covers 95 percent of the road system of Great Britain.

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