Chapter
Jun 29, 2016
Passenger Distribution Analysis for One Metro Line Based on Phone Data
Authors: Hua Meng [email protected], Donghao Yu [email protected], Yongkai Hu [email protected], Gang Zhong [email protected], and Linghui Xu [email protected]Author Affiliations
Publication: CICTP 2016
Abstract
Understanding passengers’ trip activity, especially the distribution along the metro line, is important to rail transit operation and management. Using large volumes of mobile phone user data, we derive the trip information of rail passengers. In this study, according to the generation principle and structure of the phone data, the feature of passengers’ phone data is analyzed and summarized. Based on the feature analysis, a phone-based identification method is proposed to obtain the passenger’s trip information on one metro line. By using the trip data, we analyze the distribution of a line’s passengers from the temporary and spatial dimension. The paper demonstrates the utilization of phone data in the metro system and the method we proposed contributes to the further study of passengers’ trips outside the metro.
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Published In
CICTP 2016
Pages: 932 - 942
Copyright
© 2016 American Society of Civil Engineers.
History
Published online: Jun 29, 2016
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Affiliations
Shanghai Meihui Software Co., Ltd., 12F, Galaxy Mansion, 2261 North Sichuan Rd., Shanghai, P.R.China. E-mail: [email protected]
Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast Univ., Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center for Technology and Application of Internet of Things, Nanjing 210096, China; Research Center for Internet of Mobility, Southeast Univ., Si Pai Lou #2, Nanjing 210096, China. E-mail: [email protected]
Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast Univ., Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center for Technology and Application of Internet of Things, Nanjing 210096, China; Research Center for Internet of Mobility, Southeast Univ., Si Pai Lou #2, Nanjing 210096, China. E-mail: [email protected]
Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast Univ., Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center for Technology and Application of Internet of Things, Nanjing 210096, China; Research Center for Internet of Mobility, Southeast Univ., Si Pai Lou #2, Nanjing 210096, China. E-mail: [email protected]
Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast Univ., Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center for Technology and Application of Internet of Things, Nanjing 210096, China; Research Center for Internet of Mobility, Southeast Univ., Si Pai Lou #2, Nanjing 210096, China. E-mail: [email protected]
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