Methods for Analyzing Passenger Flows During Train Traffic Disruption Using Accumulated Passenger Data

Abstract

When rescheduling train traffic after an operational disruption, train operation companies endeavor to take passenger flows into account. In this paper, a method was developed utilizing accumulated passenger data and records of arrival and departure times of each train to estimate passenger flows in such situations. The first step was to devise a visualization method to understand the relationship between rescheduling arrangements and passenger flows. Multiple regression analysis was also applied to collected data from the previous twelve months in order to develop a model for estimating passenger flows during traffic disruption. The methods are verified by applying them to actual cases of train traffic disturbances, which confirmed their reliability and effectiveness.