IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v493y2018icp430-443.html
   My bibliography  Save this article

Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city—China

Author

Listed:
  • Tang, Jinjun
  • Zhang, Shen
  • Chen, Xinqiang
  • Liu, Fang
  • Zou, Yajie

Abstract

Understanding Origin–Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K-means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone centers. A generalized cost function is further defined by considering travel distance, time and fee between each OD pair. GPS data collected from more than 1000 taxis at an interval of 30 s during one month are divided into two parts: data from first twenty days is treated as training dataset and last ten days is taken as testing dataset. The training dataset is used to calibrate model while testing dataset is used to validate model. Furthermore, three indicators, mean absolute error (MAE), root mean square error (RMSE) and mean percentage absolute error (MPAE), are applied to evaluate training and testing performance of Entropy-Maximizing model versus Gravity model. The results demonstrate Entropy-Maximizing model is superior to Gravity model. Findings of the study are used to validate the feasibility of OD distribution from taxi GPS data in urban system.

Suggested Citation

  • Tang, Jinjun & Zhang, Shen & Chen, Xinqiang & Liu, Fang & Zou, Yajie, 2018. "Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 430-443.
    • Handle: RePEc:eee:phsmap:v:493:y:2018:i:c:p:430-443
    DOI: 10.1016/j.physa.2017.11.114
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117311949
    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.2017.11.114?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. 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.
    2. 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.
    3. Tang, Jinjun & Liu, Fang & Zhang, Weibin & Zhang, Shen & Wang, Yinhai, 2016. "Exploring dynamic property of traffic flow time series in multi-states based on complex networks: Phase space reconstruction versus visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 635-648.
    4. Zhang, Shen & Tang, Jinjun & Wang, Haixiao & Wang, Yinhai & An, Shi, 2017. "Revealing intra-urban travel patterns and service ranges from taxi trajectories," Journal of Transport Geography, Elsevier, vol. 61(C), pages 72-86.
    5. Tang, Jinjun & Wang, Yinhai & Liu, Fang, 2013. "Characterizing traffic time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4192-4201.
    6. Yang, Hai & Sasaki, Tsuna & Iida, Yasunori & Asakura, Yasuo, 1992. "Estimation of origin-destination matrices from link traffic counts on congested networks," Transportation Research Part B: Methodological, Elsevier, vol. 26(6), pages 417-434, December.
    7. Tang, Jinjun & Wang, Yinhai & Wang, Hua & Zhang, Shen & Liu, Fang, 2014. "Dynamic analysis of traffic time series at different temporal scales: A complex networks approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 303-315.
    8. Yan, Ying & Zhang, Shen & Tang, Jinjun & Wang, Xiaofei, 2017. "Understanding characteristics in multivariate traffic flow time series from complex network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 149-160.
    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. Wang, Jin-Fa & He, Xuan & Si, Shuai-Zong & Zhao, Hai & Zheng, Chunyang & Yu, Hao, 2019. "Using complex network theory for temporal locality in network traffic flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 722-736.
    2. Zhang, Shen & Liu, Xin & Tang, Jinjun & Cheng, Shaowu & Qi, Yong & Wang, Yinhai, 2018. "Spatio-temporal modeling of destination choice behavior through the Bayesian hierarchical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 537-551.
    3. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Wen, Xiangxi & Tu, Congliang & Wu, Minggong & Jiang, Xurui, 2018. "Fast ranking nodes importance in complex networks based on LS-SVM method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 11-23.
    5. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2018. "Exploring dynamic evolution and fluctuation characteristics of air traffic flow volume time series: A single waypoint case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 560-571.
    6. 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.
    7. Yan, Ying & Zhang, Shen & Tang, Jinjun & Wang, Xiaofei, 2017. "Understanding characteristics in multivariate traffic flow time series from complex network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 149-160.
    8. Yang, Qiaoli & Shi, Zhongke, 2018. "Effects of the design of waiting areas on the dynamic behavior of queues at signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 181-195.
    9. Zong, Fang & Tian, Yongda & He, Yanan & Tang, Jinjun & Lv, Jianyu, 2019. "Trip destination prediction based on multi-day GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 258-269.
    10. Yang, Qiaoli & Shi, Zhongke, 2018. "The evolution process of queues at signalized intersections under batch arrivals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 413-425.
    11. Tang, Jinjun & Liang, Jian & Zhang, Shen & Huang, Helai & Liu, Fang, 2018. "Inferring driving trajectories based on probabilistic model from large scale taxi GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 566-577.
    12. Jiang, Xurui & Wen, Xiangxi & Wu, Minggong & Song, Min & Tu, Congliang, 2019. "A complex network analysis approach for identifying air traffic congestion based on independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 364-381.
    13. Sheikh, Muhammad Sameer & Regan, Amelia, 2022. "A complex network analysis approach for estimation and detection of traffic incidents based on independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    14. Zhang, Shen & Tang, Jinjun & Wang, Haixiao & Wang, Yinhai & An, Shi, 2017. "Revealing intra-urban travel patterns and service ranges from taxi trajectories," Journal of Transport Geography, Elsevier, vol. 61(C), pages 72-86.
    15. Lei Zhang & Guoxing Zhang & Zhizheng Liang & Ekene Frank Ozioko, 2018. "Multi-features taxi destination prediction with frequency domain processing," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-22, March.
    16. Yong, Nuo & Ni, Shunjiang & Shen, Shifei & Ji, Xuewei, 2020. "A study of fluctuations in subway traffic from the control properties of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    17. Guo, Yajuan & Yang, Licai & Hao, Shenxue & Gao, Jun, 2019. "Dynamic identification of urban traffic congestion warning communities in heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 98-111.
    18. Yang, Qiaoli & Shi, Zhongke & Tang, Min-an & Gao, Fengyang & Yu, Shaowei, 2019. "Modeling the permissive-only left-turn queue at signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 315-325.
    19. Liu, Fagui & Zhang, Zhijie, 2017. "Adaptive density trajectory cluster based on time and space distance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 41-56.
    20. Susan Jia Xu & Mehdi Nourinejad & Xuebo Lai & Joseph Y. J. Chow, 2018. "Network Learning via Multiagent Inverse Transportation Problems," Service Science, INFORMS, vol. 52(6), pages 1347-1364, 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:493:y:2018:i:c:p:430-443. 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.