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Zhou, Meng; Wang, Donggen; Li, Qingquan; Yue, Yang; Tu, Wei; Cao, Rui
Transportation research. Part C, Emerging technologies, 02/2017, Volume: 75Journal Article
•Transport impacts of weather using smartcard data and meteorological observations are explored.•Weather impact on hourly public transit ridership is examined.•Weather impact on the ridership at individual metro station is investigated.•Regular transit users’ response to weather conditions is explored.•Statistical models are developed to quantify these impacts. The existing studies concerning the influence of weather on public transport have mainly focused on the impacts of average weather conditions on the aggregate ridership of public transit. Not much research has examined these impacts at disaggregate levels. This study aims to fill this gap by accounting for intra-day variations in weather as well as public transport ridership and investigating the effect of weather on the travel behavior of individual public transit users. We have collected smart card data for public transit and meteorological records from Shenzhen, China for the entire month of September 2014. The data allow us to establish association between the system-wide public transit ridership and weather condition on not only daily, but also hourly basis and for each metro station. In addition, with the detailed trip records of individual card holders, the travel pattern by public transit are constructed for card holders and this pattern is linked to the weather conditions he/she has experienced. Multivariate modeling approach is applied to analyze the influence of weather on public transit ridership and the travel behavior of regular transit users. Results show that some weather elements have more influence than others on public transportation. Metro stations located in urban areas are more vulnerable to outdoor weather in regard to ridership. Regular transit users are found to be rather resilient to changes in weather conditions. Findings contribute to a more in-depth understanding of the relationship between everyday weather and public transit travels and also provide valuable information for short-term scheduling in transit management.
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