Open AccessFinite mixture survival model for examining the variability of urban arterial travel time for buses, passenger cars and taxis
Author(s) -
Zhong Xinzhi,
Zou Yajie,
Dong Zhi,
Yuan Shaoxin,
Ijaz Muhammad
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0504
Subject(s) - taxis , travel time , transport engineering , trips architecture , population , travel behavior , geography , statistics , computer science , econometrics , engineering , mathematics , environmental health , medicine
Examining the travel time variability (TTV) of buses, passenger cars and taxis is essential to obtain reliable travel time in urban daily trips. TTV analyses of three travel modes are conducted using travel time data collected on two urban arterial roads in Xi'an City. Firstly, the TTV is evaluated using statistical indexes. The results reveal that the TTV differs from vehicle to vehicle, period to period and site to site. Secondly, the finite mixture survival model is proposed to address the heterogeneity of travel time data by decomposing the population into several sub‐populations. Wasserstein distance and Kolmogorov–Smirnov test are used to further compare the sub‐populations of different vehicle types during different periods on different roads. Finally, based on the model analysis, it can be found that the finite mixture survival model is an accurate tool to examine the variability by capturing the heterogeneity of travel time data. The difference among the sub‐populations suggests different travel behaviours. It concludes that more diverse travel behaviours result in higher TTV. An accurate investigation on TTV is valuable for travellers’ mode choices and transportation management agencies to obtain reliable travel time information and improve traffic efficiency.