Abstract
Passenger flow prediction is important for the planning, design and decision-making of urban rail transit lines. Weather is an important factor that affects the passenger flow of rail transit line by changing the travel mode choice of urban residents. A number of previous researches focused on analyzing the effects of weather (e.g. rain, snow, and temperature) on public transport ridership, but the effects on rail transit line yet remain largely unexplored This study aims to explore the influence of weather on ridership of urban rail transit lines, taking Chengdu rail transit line 1 and line 2 as examples. Linear regression method was used to develop models for estimating the daily passenger flow of different rail transit lines under different weather conditions. The results show that for Chengdu rail transit line 1, the daily ridership rate of rail transit increases with increasing temperature. While, for Chengdu rail transit line 2, the daily ridership rate of rail transit decreases with increasing wind power. The research findings can provide effective strategies to rail transit operators to deal with the fluctuation in daily passenger flow.
Highlights
The passenger flow estimation of urban rail transit is widely used as the foundation for the planning, design, and daily operations of rail transit
If |t| is greater than 1.96 at a 5% significance level, we are 95% confident that the variable has a significant impact on the daily passenger flow in rail transit lines, otherwise the variable will be eliminated
This study performed large-scale data analysis on the data of daily passenger flow and weather elements to explore the impacts of weather factors on usage of rail transit line
Summary
The passenger flow estimation of urban rail transit is widely used as the foundation for the planning, design, and daily operations of rail transit. Weather factors are not usually presented in the existing models for estimating rail transit line ridership, which results in an insufficient or excessive estimation in the design stage, and unexpected large fluctuations in operation stage. It is essential to identify the impacts of weather factors on passenger flow of rail transit line. The relevant research mainly includes three aspects: data preprocessing of passenger flow [1, 2] quantitative analysis of impact factors [3,4,5,6,7] and development of estimation models [8, 9]
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