A theoretical analysis of the influence of time of day and weather conditions on the metro passenger arrival rate utilizing a multiple linear regression model.

The metropolitan transit system is a critical component of urban transportation, offering a fast, reliable, and environmentally friendly mode of travel in densely populated cities. This research delves into the factors influencing metro passengers' arrival rates at Yujiatou Station on Wuhan Metro Line 5 in China, focusing on the influence of time of day and weather conditions. The study addresses a significant research gap in understanding metro passengers' dynamics by utilizing questionnaires, direct field observation, and statistical techniques, including multiple linear regression for data analysis. The results revealed meaningful relationships, such as the correlation between rainy evening weather and arrival rates and a moderate positive correlation between time of day and arrival rates, with the model achieving an R-squared value of approximately 40%. The study also highlights the individual impacts of weather and time of day on predicting metro passenger arrival rates. The research suggests that adjusting service schedules based on weather conditions and peak times could help manage passenger flow, which has practical implications for transportation planners, metro operators, and passengers, informing strategies for optimizing service schedules and enhancing the overall user experience. These findings can contribute to sustainable transportation initiatives and urban development goals by improving urban transportation systems.