Abstract
In recent years, cities have been increasingly confronted with frequent and severe extreme weather events, such as heavy rainfall, high temperatures, and strong winds. These extreme weather conditions not only impact urban transportation operations but also directly affect passengers' travel patterns and behaviors. In this context, gaining a deeper understanding of the mechanisms through which weather factors influence urban subway passenger flow becomes crucial. This study aims to investigate the relationship between passenger flow and weather factors, and provide valuable insights for urban rail transit management to enhance proactive decision-making. To achieve this research objective, we first establish a framework for studying the impact of weather on passenger flow. Based on this framework, an analysis is conducted using passenger flow data and weather data from Beijing Metro Line 4. The findings of this study reveal significant effects of different weather factors on subway passenger flow. Increasing severity of weather conditions and higher wind speeds have a negative influence on passenger flow, leading to a decrease in ridership. Conversely, a significant positive correlation is observed between the highest temperature and subway passenger flow, indicating that as the highest temperature rises, the passenger volume also increases.
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More From: Transactions on Computer Science and Intelligent Systems Research
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