Statistical modelling of bus travel time with Burr distribution

A better understanding of the travel time distribution shape or pattern could improve the decision made by the transport operator to estimate the travel time required for the vehicle to travel from one place to another. Finding the most appropriate distribution to represent the day-to-day travel tim...

Full description

Saved in:
Bibliographic Details
Published in:ITM web of conferences 2021, Vol.36, p.1011
Main Authors: Low, Victor Jian Ming, Khoo, Hooi Ling, Khoo, Wooi Chen
Format: Article
Language:English
Subjects:
Automatic vehicle location
Buses (vehicles)
Criteria
Maximum likelihood estimation
Parameter estimation
Performance assessment
Reliability analysis
Statistical models
Travel time
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A better understanding of the travel time distribution shape or pattern could improve the decision made by the transport operator to estimate the travel time required for the vehicle to travel from one place to another. Finding the most appropriate distribution to represent the day-to-day travel time variation of an individual link of a bus route is the main purpose of this study. Klang Valley, Malaysia is the study area for the research. A consecutive of 7 months ten bus routes automatic vehicle location (AVL) data are used to examine the distribution performance. The leading distribution proposed for the research is the Burr distribution. Both symmetrical and asymmetrical distributions that have been proposed in existing studies are also used for comparison purposes. Maximum likelihood estimation is applied for parameter estimation while loglikelihood value, Akaike information criterion (AIC) and Bayesian information criterion (BIC) are applied for performance assessment of the distributions. Promising results are obtained by the leading model in all different kinds of operating environment and could be treated as the preliminary preparation for further reliability analysis.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20213601011