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Human mobility in space from three modes of public transportation

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  • Jiang, Shixiong
  • Guan, Wei
  • Zhang, Wenyi
  • Chen, Xu
  • Yang, Liu

Abstract

The human mobility patterns have drew much attention from researchers for decades, considering about its importance for urban planning and traffic management. In this study, the taxi GPS trajectories, smart card transaction data of subway and bus from Beijing are utilized to model human mobility in space. The original datasets are cleaned and processed to attain the displacement of each trip according to the origin and destination locations. Then, the Akaike information criterion is adopted to screen out the best fitting distribution for each mode from candidate ones. The results indicate that displacements of taxi trips follow the exponential distribution. Besides, the exponential distribution also fits displacements of bus trips well. However, their exponents are significantly different. Displacements of subway trips show great specialties and can be well fitted by the gamma distribution. It is obvious that human mobility of each mode is different. To explore the overall human mobility, the three datasets are mixed up to form a fusion dataset according to the annual ridership proportions. Finally, the fusion displacements follow the power-law distribution with an exponential cutoff. It is innovative to combine different transportation modes to model human mobility in the city.

Suggested Citation

  • Jiang, Shixiong & Guan, Wei & Zhang, Wenyi & Chen, Xu & Yang, Liu, 2017. "Human mobility in space from three modes of public transportation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 227-238.
    • Handle: RePEc:eee:phsmap:v:483:y:2017:i:c:p:227-238
    DOI: 10.1016/j.physa.2017.04.182
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    References listed on IDEAS

    as
    1. Kang, Chaogui & Ma, Xiujun & Tong, Daoqin & Liu, Yu, 2012. "Intra-urban human mobility patterns: An urban morphology perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1702-1717.
    2. Ryuichi Kitamura & Cynthia Chen & Ram Pendyala & Ravi Narayanan, 2000. "Micro-simulation of daily activity-travel patterns for travel demand forecasting," Transportation, Springer, vol. 27(1), pages 25-51, February.
    3. Baldwin Hess, Daniel, 2009. "Access to Public Transit and Its Influence on Ridership for Older Adults in Two U.S. Cities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(1), pages 3-27.
    4. Yu Liu & Zhengwei Sui & Chaogui Kang & Yong Gao, 2014. "Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    5. Liu, Chengxi & Susilo, Yusak O. & Karlström, Anders, 2015. "The influence of weather characteristics variability on individual’s travel mode choice in different seasons and regions in Sweden," Transport Policy, Elsevier, vol. 41(C), pages 147-158.
    6. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    7. Tang, Jinjun & Liu, Fang & Wang, Yinhai & Wang, Hua, 2015. "Uncovering urban human mobility from large scale taxi GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 140-153.
    8. Cai, Hua & Zhan, Xiaowei & Zhu, Ji & Jia, Xiaoping & Chiu, Anthony S.F. & Xu, Ming, 2016. "Understanding taxi travel patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 590-597.
    9. Singhal, Abhishek & Kamga, Camille & Yazici, Anil, 2014. "Impact of weather on urban transit ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 379-391.
    10. Arana, P. & Cabezudo, S. & Peñalba, M., 2014. "Influence of weather conditions on transit ridership: A statistical study using data from Smartcards," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 1-12.
    11. Sun, J.B. & Yuan, J. & Wang, Y. & Si, H.B. & Shan, X.M., 2011. "Exploring space–time structure of human mobility in urban space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 929-942.
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    Cited by:

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    2. Xia, Dong & Zheng, Linjiang & Tang, Yi & Cai, Xiaolin & Chen, Li & Sun, Dihua, 2022. "Dynamic traffic prediction for urban road network with the interpretable model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    3. Zheng, Linjiang & Xia, Dong & Zhao, Xin & Tan, Longyou & Li, Hang & Chen, Li & Liu, Weining, 2018. "Spatial–temporal travel pattern mining using massive taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 24-41.
    4. Zhou, Yufeng & Li, Zihao & Meng, Yangyang & Li, Zhongwen & Zhong, Maohua, 2021. "Analyzing spatio-temporal impacts of extreme rainfall events on metro ridership characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    5. Xia, Dawen & Jiang, Shunying & Yang, Nan & Hu, Yang & Li, Yantao & Li, Huaqing & Wang, Lin, 2021. "Discovering spatiotemporal characteristics of passenger travel with mobile trajectory big data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    6. Sui, Yi & Shao, Fengjing & Yu, Xiang & Sun, Rencheng & Li, Shujing, 2019. "Public transport network model based on layer operations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 984-995.
    7. Yanyan Chen & Zheng Zhang & Tianwen Liang, 2019. "Assessing Urban Travel Patterns: An Analysis of Traffic Analysis Zone-Based Mobility Patterns," Sustainability, MDPI, vol. 11(19), pages 1-15, October.

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