Holding Boarding Passengers to Improve Train Operation on Basis of an Economic Dwell Time Model

Abstract

This paper aims to explain the factors that determine the dwell time of subway trains in Santiago, Chile. On the basis of morning rush-hour video recordings of Line 1’s most critically congested station, Baquedano, explanatory variables were selected to adjust a mathematical model. The purpose behind this model was to identify which factors could be managed to increase the system’s overall operation so as to reduce dwell times and improve passengers’ traveling experience. The model was obtained by adjusting a linear regression that considered the number of boarding passengers, the number of alighting passengers multiplied by the platform’s occupancy level before and after the exchange, and the density inside the train (which had an exponential impact on dwell time). The model’s correlation coefficient was .65, and the train’s passenger density was found to be the most significant variable, as it explained 73.6% of the trains’ average dwell time. In contrast to what might have been expected, the interaction between passengers getting off the train and the platform’s occupancy level explained only 2.1% of the total dwell time. The conclusion of this study was that the passenger’s overall traveling experience could be improved by implementing a passenger management system throughout the platform and slightly reducing the dwell time of the trains. As Baquedano Station is one of the busiest stations of the subway network, reductions in the dwell time of trains could increase overall departure frequencies, which would increase the line capacity and improve network operation of all downstream stations.