Statistical modelling of bus travel time with Burr distribution

• 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
• ISSN: 2271-2097; 2431-7578; 2271-2097
• DOI: 10.1051/itmconf/20213601011

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.