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.
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