The Impact of Weather Conditions on Transit Ridership Using Quantile Regression Analysis

Abstract

This study aimed to figure out the weather conditions’ influence on ridership of public transit by mode with the method of Quantile Regression analysis (QR) based on data of busans` transportation cards and weather from 2011 to 2015. The QR was conducted on city bus, subway, between city bus and city bus, and between city bus and subway. The result showed that temperature had positive (+) influence and that, humidity and rainfall had negative (-) one. Temperature was a key factor of ridership in city bus and transfer between city buses. For the transfer between the city bus and subway, humidity was the major element influencing the ridership. In both factors, as quantiles go up, quantile coefficients go down. In other words, when the quantile is low, the ridership was more influenced by temperature and humidity. The rainfall is the main reason for change in the ridership of the subway. The higher the quantile is, the bigger the quantile coefficient is. In other words, when the quantile is high, the ridership was more influenced by rainfall. In terms of the day of week, the temperature and humidity have more influence on the ridership of weekdays, and the rainfall does on that of holidays and weekends.

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