IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v609y2023ics0378437122009499.html
   My bibliography  Save this article

Exploring the topological characteristics of urban trip networks based on taxi trajectory data

Author

Listed:
  • Li, Ze-Tao
  • Nie, Wei-Peng
  • Cai, Shi-Min
  • Zhao, Zhi-Dan
  • Zhou, Tao

Abstract

As an essential mode of travel for city residents, taxis play a significant role in meeting travel demands in an urban city. Understanding the modal characteristics of taxis is vital to addressing many difficulties regarding urban sustainability. The movement trajectory of taxis reflects not only the operating features of taxis themselves but also urban structure and human mobility. In this work, the taxi trajectory data of Chengdu and New York City is processed, and the corresponding urban trip networks are constructed based on geographic information systems. We empirically and systematically analyze these urban trip networks according to the network hierarchy based on complex network theory. First, we studied the low-order organization of the urban trip networks (i.e., degree distribution, cluster-degree coefficient, rich-club coefficient, and so on.). We uncover the nontrivial relationship between network density and trip distance and find that the urban trip network in Chengdu is more heterogeneous than that in New York City. Second, we investigate the meso-order organization of the urban trip networks by using community detection. The community detection results show that the community boundaries are more or less mismatched with the administrative boundaries. Finally, we detect the higher-order organizations of the urban trip networks and find some critical nodes and regions. These empirical results from the perspective of complex networks provide insight to better understand the urban structure and human mobility, and potentially amend urban planning.

Suggested Citation

  • Li, Ze-Tao & Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2023. "Exploring the topological characteristics of urban trip networks based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    • Handle: RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122009499
    DOI: 10.1016/j.physa.2022.128391
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122009499
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.128391?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jianjun Qin & Maohui Zheng, 2017. "New York city taxi trips: Dynamic networks following inconsistent power law," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(07), pages 1-19, July.
    2. Zhao, Zhi-Dan & Gao, Ya-Chun & Cai, Shi-Min & Zhou, Tao, 2016. "Dynamic patterns of academic forum activities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 117-124.
    3. Yang, Yu & He, Ze & Song, Zouying & Fu, Xin & Wang, Jianwei, 2018. "Investigation on structural and spatial characteristics of taxi trip trajectory network in Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 755-766.
    4. Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2022. "Revealing mobility pattern of taxi movements with its travel trajectory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    5. Markus Schläpfer & Lei Dong & Kevin O’Keeffe & Paolo Santi & Michael Szell & Hadrien Salat & Samuel Anklesaria & Mohammad Vazifeh & Carlo Ratti & Geoffrey B. West, 2021. "The universal visitation law of human mobility," Nature, Nature, vol. 593(7860), pages 522-527, May.
    6. Brodeur, Abel & Nield, Kerry, 2018. "An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 1-16.
    7. Thomas Louail & Maxime Lenormand & Miguel Picornell & Oliva García Cantú & Ricardo Herranz & Enrique Frias-Martinez & José J. Ramasco & Marc Barthelemy, 2015. "Uncovering the spatial structure of mobility networks," Nature Communications, Nature, vol. 6(1), pages 1-8, May.
    8. Hu, Beibei & Zhang, Shuang & Ding, Yang & Zhang, Min & Dong, Xianlei & Sun, Huijun, 2021. "Research on the coupling degree of regional taxi demand and social development from the perspective of job–housing travels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    9. Hsing Liu & Ying-Hsing Chen & Jiann-Shing Lih, 2015. "Crossover from exponential to power-law scaling for human mobility pattern in urban, suburban and rural areas," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(5), pages 1-7, May.
    10. Yao, Can-Zhong & Lin, Ji-Nan, 2016. "A study of human mobility behavior dynamics: A perspective of a single vehicle with taxi," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 51-58.
    11. 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.
    12. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    13. Laura Alessandretti & Ulf Aslak & Sune Lehmann, 2020. "The scales of human mobility," Nature, Nature, vol. 587(7834), pages 402-407, November.
    14. Aleix Bassolas & Hugo Barbosa-Filho & Brian Dickinson & Xerxes Dotiwalla & Paul Eastham & Riccardo Gallotti & Gourab Ghoshal & Bryant Gipson & Surendra A. Hazarie & Henry Kautz & Onur Kucuktunc & Alli, 2019. "Hierarchical organization of urban mobility and its connection with city livability," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    15. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    16. Dong, Xianlei & Zhang, Min & Zhang, Shuang & Shen, Xinyi & Hu, Beibei, 2019. "The analysis of urban taxi operation efficiency based on GPS trajectory big data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    17. Beibei Hu & Yue Sun & Huijun Sun & Xianlei Dong, 2020. "A Contrastive Study on Travel Costs of Car-Sharing and Taxis Based on GPS Trajectory Data," IJERPH, MDPI, vol. 17(24), pages 1-28, December.
    18. Minjie Wang & Su Yang & Yi Sun & Jun Gao, 2017. "Human mobility prediction from region functions with taxi trajectories," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-23, November.
    19. Chengbin Peng & Xiaogang Jin & Ka-Chun Wong & Meixia Shi & Pietro Liò, 2012. "Collective Human Mobility Pattern from Taxi Trips in Urban Area," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-8, April.
    20. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2022. "Revealing mobility pattern of taxi movements with its travel trajectory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    2. Shi, Shuyang & Wang, Lin & Wang, Xiaofan, 2022. "Uncovering the spatiotemporal motif patterns in urban mobility networks by non-negative tensor decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    3. Xu Mengqiao & Zhang Ling & Li Wen & Xia Haoxiang, 2017. "Mobility Pattern of Taxi Passengers at Intra-Urban Scale: Empirical Study of Three Cities," Journal of Systems Science and Information, De Gruyter, vol. 5(6), pages 537-555, December.
    4. 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.
    5. Tang, Jinjun & Zhang, Shen & Zhang, Wenhui & Liu, Fang & Zhang, Weibin & Wang, Yinhai, 2016. "Statistical properties of urban mobility from location-based travel networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 694-707.
    6. He, Zhengbing, 2020. "Spatial-temporal fractal of urban agglomeration travel demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    7. Rongxiang Su & Zhixiang Fang & Ningxin Luo & Jingwei Zhu, 2018. "Understanding the Dynamics of the Pick-Up and Drop-Off Locations of Taxicabs in the Context of a Subsidy War among E-Hailing Apps," Sustainability, MDPI, vol. 10(4), pages 1-24, April.
    8. Laura Alessandretti & Luis Guillermo Natera Orozco & Meead Saberi & Michael Szell & Federico Battiston, 2023. "Multimodal urban mobility and multilayer transport networks," Environment and Planning B, , vol. 50(8), pages 2038-2070, October.
    9. Jiang, Jincheng & Xu, Zhihua & Zhang, Zhenxin & Zhang, Jie & Liu, Kang & Kong, Hui, 2023. "Revealing the fractal and self-similarity of realistic collective human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    10. Tong Zhou & Xintao Liu & Zhen Qian & Haoxuan Chen & Fei Tao, 2019. "Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points," Sustainability, MDPI, vol. 11(23), pages 1-20, December.
    11. Rezapour, Shabnam & Baghaian, Atefe & Naderi, Nazanin & Sarmiento, Juan P., 2023. "Infection transmission and prevention in metropolises with heterogeneous and dynamic populations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 113-138.
    12. 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.
    13. Huang, Zhiren & Wang, Pu & Zhang, Fan & Gao, Jianxi & Schich, Maximilian, 2018. "A mobility network approach to identify and anticipate large crowd gatherings," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 147-170.
    14. Zhang, Xiaohu & Xu, Yang & Tu, Wei & Ratti, Carlo, 2018. "Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage," Journal of Transport Geography, Elsevier, vol. 70(C), pages 78-90.
    15. Zhang, Xiaohu, 2021. "Beyond expected regularity of aggregate urban mobility: A case study of ridesourcing service," Journal of Transport Geography, Elsevier, vol. 95(C).
    16. Jungmin Kim & Juyong Park & Wonjae Lee, 2018. "Why do people move? Enhancing human mobility prediction using local functions based on public records and SNS data," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-29, February.
    17. Ruixi Dong & Fengying Yan, 2021. "Revealing Characteristics of the Spatial Structure of Megacities at Multiple Scales with Jobs-Housing Big Data: A Case Study of Tianjin, China," Land, MDPI, vol. 10(11), pages 1-20, October.
    18. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    19. Toru Nakamura & Toru Takumi & Atsuko Takano & Fumiyuki Hatanaka & Yoshiharu Yamamoto, 2013. "Characterization and Modeling of Intermittent Locomotor Dynamics in Clock Gene-Deficient Mice," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
    20. Fangye Du & Jiaoe Wang & Liang Mao & Jian Kang, 2024. "Daily rhythm of urban space usage: insights from the nexus of urban functions and human mobility," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122009499. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.