Metro transit is the core of urban transportation, and the mobility analysis of metro ridership can contribute to enhance the overall service level of the metro transit. Researchers studying metro ridership are focused on the spatiotemporal distribution characteristics of the ridership in the underground system of metro station by metro smart card data. However, limited by lack of travel mobility chain of ridership integrity, their activity patterns cannot be used to identify the heterogeneity of metro ridership's origin and transfer travel mode. In our research, we applied full spatiotemporal coverage of mobile phone data to identify the complete travel mobility of metro ridership in the perspective of ground and underground transit. First, the mobility of the boarding and alighting stations was extracted and the order of the transfer station was then extracted. Second, relying on the ridership flow identification method, the aboveground origin and destination of the ridership outside the metro system were extracted, and their transferred traffic mode was identified. The empirical results have shown that our proposed framework can accurately analyze the mobility patterns of metro ridership in an aboveground area and underground station.
Citation: Jiping Xing, Xiaohong Jiang, Yu Yuan, Wei Liu. Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers[J]. Electronic Research Archive, 2024, 32(7): 4472-4494. doi: 10.3934/era.2024202
Metro transit is the core of urban transportation, and the mobility analysis of metro ridership can contribute to enhance the overall service level of the metro transit. Researchers studying metro ridership are focused on the spatiotemporal distribution characteristics of the ridership in the underground system of metro station by metro smart card data. However, limited by lack of travel mobility chain of ridership integrity, their activity patterns cannot be used to identify the heterogeneity of metro ridership's origin and transfer travel mode. In our research, we applied full spatiotemporal coverage of mobile phone data to identify the complete travel mobility of metro ridership in the perspective of ground and underground transit. First, the mobility of the boarding and alighting stations was extracted and the order of the transfer station was then extracted. Second, relying on the ridership flow identification method, the aboveground origin and destination of the ridership outside the metro system were extracted, and their transferred traffic mode was identified. The empirical results have shown that our proposed framework can accurately analyze the mobility patterns of metro ridership in an aboveground area and underground station.
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Figures(9) / Tables(4)
Jiping Xing, Xiaohong Jiang, Yu Yuan, Wei Liu. Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers[J]. Electronic Research Archive, 2024, 32(7): 4472-4494. doi: 10.3934/era.2024202
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