TITLE:
Contributing Factors for Train Delays during Morning Rush Hour in Japanese Metropolitan Areas
AUTHORS:
Keigo Ohshima, Kayoko Yamamoto
KEYWORDS:
Train Delay, Morning Rush Hour, Train Line Network, Statistical Analy-sis, Standard Multiple Regression Analysis, Logistic Regression Analysis
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.10 No.2,
March
25,
2020
ABSTRACT: The present study aims to reveal the contributing factors for train
delays in Tokyo metropolitan area by conducting statistical analyses, focusing
on passenger trains, and using a variety of information by including data concerning train cars, stations,
passengers, tracks and working timetables as explanatory variables. The present
study conducted 2 types of statistical analyses including the standard multiple
regression analysis and the logistic regression analysis by setting “average
delay time” which indicates the quantitative conditions of delays, and
“occurrence of delays” which indicates the qualitative condition, as objective
variables. According to the results of the logistic regression analysis, the
possibility of direct operations increasing the delay occurrence rate was
quantitatively indicated. Therefore, direct operations are regarded as a
contributing factor for train delays concerning metropolitan areas in recent
years. Additionally, it was confirmed that the concentration of demand on
terminal stations is also a contributing factor for train delays. On the other
hand, it is certain that direct operations contribute to improving the convenience of passengers as well as the operational efficiency of
train cars. Therefore, it would be ideal to resolve delays by easing the
concentration of demands which may be accomplished by recommending off-peak
commuting as well as adjustments to the working timetables.