IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v535y2019ics0378437119313275.html
   My bibliography  Save this article

Active lane-changing model of vehicle in B-type weaving region based on potential energy field theory

Author

Listed:
  • Ma, Yanli
  • Zhang, Peng
  • Hu, Baoyu

Abstract

To define lane-changing time accurately and quantitatively, the influence of vehicle spacing on lane-changing time was studied using cars. Taking into account the influence of surrounding vehicles’ spacing on lane-changing, a vehicle lane-changing time model on an urban road B-type weaving section based on a potential energy field theory was proposed. The model quantitatively illustrated the influence of surrounding vehicles’ spacing on lane-changing lateral acceleration and then deduced the relationship between the lateral displacement, longitudinal displacement and time of the lane-changing vehicle. By using the aerial data of passenger cars lane-changing in the weaving area of an urban trunk road, the parameters in the model were calibrated and the lane-changing trajectory of vehicles simulated by the model was tested. It is found that the accuracy of the lane-changing model to quantitatively define the transverse acceleration while changing lanes and the spacing between constrained regions reaches 90%, and the fitting degree between simulated lane change trajectory and actual lane change trajectory is over 90%. The results show that the vehicle lane-change model based on the potential energy field theory can effectively simulate the relationship between vehicle lane-change time and lateral and longitudinal displacement and can provide theoretical and technical support for traffic simulation and multi-vehicle interaction.

Suggested Citation

  • Ma, Yanli & Zhang, Peng & Hu, Baoyu, 2019. "Active lane-changing model of vehicle in B-type weaving region based on potential energy field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313275
    DOI: 10.1016/j.physa.2019.122291
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119313275
    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.2019.122291?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 & 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.
    2. Gipps, P. G., 1986. "A model for the structure of lane-changing decisions," Transportation Research Part B: Methodological, Elsevier, vol. 20(5), pages 403-414, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Changxi & Li, Dong, 2023. "A review of vehicle lane change research," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    2. Chen, Tianyi & Shi, Xiupeng & Wong, Yiik Diew, 2021. "A lane-changing risk profile analysis method based on time-series clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    3. Song Fang & Linghong Shen & Jianxiao Ma & Chubo Xu, 2022. "Study on the Design of Variable Lane Demarcation in Urban Tunnels," Sustainability, MDPI, vol. 14(9), pages 1-12, May.
    4. Yuning Wang & Shuocheng Yang & Jinhao Li & Shaobing Xu & Jianqiang Wang, 2023. "An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    5. Wang, Zhangu & Guan, Changming & Zhao, Ziliang & Zhao, Jun & Qi, Chen & Hui, Zilaing, 2024. "Expressway lane change strategy of autonomous driving based on prior knowledge and data-driven," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    6. Li, Linheng & Gan, Jing & Zhou, Kun & Qu, Xu & Ran, Bin, 2020. "A novel lane-changing model of connected and automated vehicles: Using the safety potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    7. Ma, Yanli & Lv, Zhiliang & Zhang, Peng & Chan, Ching-Yao, 2021. "Impact of lane changing on adjacent vehicles considering multi-vehicle interaction in mixed traffic flow: A velocity estimating model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).

    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. Mingmin Guo & Zheng Wu & Huibing Zhu, 2018. "Empirical study of lane-changing behavior on three Chinese freeways," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-22, January.
    2. He, Jia & He, Zhengbing & Fan, Bo & Chen, Yanyan, 2020. "Optimal location of lane-changing warning point in a two-lane road considering different traffic flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. 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.
    4. Ziakopoulos, Apostolos & Oikonomou, Maria G. & Vlahogianni, Eleni I. & Yannis, George, 2021. "Quantifying the implementation impacts of a point to point automated urban shuttle service in a large-scale network," Transport Policy, Elsevier, vol. 114(C), pages 233-244.
    5. Tang, Jinjun & Bi, Wei & Liu, Fang & Zhang, Wenhui, 2021. "Exploring urban travel patterns using density-based clustering with multi-attributes from large-scaled vehicle trajectories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    6. Kanagaraj, Venkatesan & Treiber, Martin, 2018. "Self-driven particle model for mixed traffic and other disordered flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1-11.
    7. Jin, Wen-Long, 2012. "A kinematic wave theory of multi-commodity network traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 1000-1022.
    8. Changxi Ma & Ruichun He & Wei Zhang, 2018. "Path optimization of taxi carpooling," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-15, August.
    9. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    10. Ci, Yusheng & Wu, Lina & Zhao, Jiafa & Sun, Yichen & Zhang, Guohui, 2019. "V2I-based car-following modeling and simulation of signalized intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 672-679.
    11. 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.
    12. Sermpis, Dimitris, 2007. "The Influence of Geometry on Operational Performance of Signal-Controlled Junctions," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 46(1).
    13. Ma, Yanli & Lv, Zhiliang & Zhang, Peng & Chan, Ching-Yao, 2021. "Impact of lane changing on adjacent vehicles considering multi-vehicle interaction in mixed traffic flow: A velocity estimating model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    14. Tang, Jinjun & Yang, Yifan & Qi, Yong, 2018. "A hybrid algorithm for Urban transit schedule optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 745-755.
    15. Melo, Sandra & Macedo, Joaquim & Baptista, Patrícia, 2019. "Capacity-sharing in logistics solutions: A new pathway towards sustainability," Transport Policy, Elsevier, vol. 73(C), pages 143-151.
    16. Shi, Kunsong & Wu, Yuankai & Shi, Haotian & Zhou, Yang & Ran, Bin, 2022. "An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    17. Matteo Richiardi, 2003. "The New Italian Road Code and the Virtues of the ‘Shame Lane’," LABORatorio R. Revelli Working Papers Series 31, LABORatorio R. Revelli, Centre for Employment Studies.
    18. Rockwell International Science Center, 1992. "Potential Payoffs From Ivhs: A Framework For Analysis," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7gf7j8n2, Institute of Transportation Studies, UC Berkeley.
    19. Li, Linheng & Gan, Jing & Zhou, Kun & Qu, Xu & Ran, Bin, 2020. "A novel lane-changing model of connected and automated vehicles: Using the safety potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    20. Xu, Ting & Jiang, Ruisen & Wen, Changlei & Liu, Meijun & Zhou, Jiehan, 2019. "A hybrid model for lane change prediction with V2X-based driver assistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).

    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:535:y:2019:i:c:s0378437119313275. 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.