IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v649y2024ics0378437124004552.html
   My bibliography  Save this article

Traffic flow model considering the dynamics prediction of the leading vehicle

Author

Listed:
  • Pogrebnyak, Maxim

Abstract

Traffic flow modeling has become increasingly important in today’s society due to the growing number of vehicles on the roads, leading to congestion and traffic incidents. Mathematical modeling can aid in the planning and optimization of transportation systems, enhancing overall efficiency and safety. The main result of this study is a mathematical model that describes the dynamics of multiple vehicles, taking into account the prediction of the leading vehicle’s behavior. The model is formulated as a system of delay differential equations. A computer program has been developed based on this model, which simulates traffic flow in various road scenarios. The simulation results are consistent with observed data from real traffic flows.

Suggested Citation

  • Pogrebnyak, Maxim, 2024. "Traffic flow model considering the dynamics prediction of the leading vehicle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 649(C).
  • Handle: RePEc:eee:phsmap:v:649:y:2024:i:c:s0378437124004552
    DOI: 10.1016/j.physa.2024.129946
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124004552
    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.2024.129946?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. Zhai, Cong & Li, Kening & Zhang, Ronghui & Peng, Tao & Zong, Changfu, 2024. "Phase diagram in multi-phase heterogeneous traffic flow model integrating the perceptual range difference under human-driven and connected vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    2. Hossain, Md. Anowar & Tanimoto, Jun, 2022. "A microscopic traffic flow model for sharing information from a vehicle to vehicle by considering system time delay effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Lily Elefteriadou, 2014. "An Introduction to Traffic Flow Theory," Springer Optimization and Its Applications, Springer, edition 127, number 978-1-4614-8435-6, July.
    4. Zhai, Cong & Wu, Weitiao & Xiao, Yingping, 2023. "The jamming transition of multi-lane lattice hydrodynamic model with passing effect," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    5. Hosen, Md. Zakir & Hossain, Md. Anowar & Tanimoto, Jun, 2024. "Traffic model for the dynamical behavioral study of a traffic system imposing push and pull effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    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. Kang, Yi-rong & Tian, Chuan, 2024. "A new curved road lattice model integrating the multiple prediction effect under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    2. Peng, Guanghan & Wang, Wanlin & Tan, Huili, 2023. "Chaotic jam and phase transitions in heterogeneous lattice model integrating the delay characteristics difference with passing effect under autonomous and human-driven vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    3. Zhai, Cong & Li, Kening & Zhang, Ronghui & Peng, Tao & Zong, Changfu, 2024. "Phase diagram in multi-phase heterogeneous traffic flow model integrating the perceptual range difference under human-driven and connected vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    4. Kerner, Boris S., 2016. "Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 700-747.
    5. Zhai, Cong & Zhang, Ronghui & Peng, Tao & Zhong, Changfu & Xu, Hongguo, 2023. "Heterogeneous lattice hydrodynamic model and jamming transition mixed with connected vehicles and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    6. Peng, Guanghan & Xu, Mingzuo & Tan, Huili, 2024. "Phase transition in a new heterogeneous macro continuum model of traffic flow under rain and snow weather environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    7. Hosen, Md. Zakir & Hossain, Md. Anowar & Tanimoto, Jun, 2024. "Traffic model for the dynamical behavioral study of a traffic system imposing push and pull effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    8. Qi, Weiwei & Ma, Siwei & Fu, Chuanyun, 2023. "An improved car-following model considering the influence of multiple preceding vehicles in the same and two adjacent lanes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P2).
    9. Kerner, Boris S. & Koller, Micha & Klenov, Sergey L. & Rehborn, Hubert & Leibel, Michael, 2015. "The physics of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 365-397.
    10. Hu, Junjie & Hu, Cheng & Yang, Jiayu & Bai, Jun & Lee, Jaeyoung Jay, 2024. "Do traffic flow states follow Markov properties? A high-order spatiotemporal traffic state reconstruction approach for traffic prediction and imputation," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    11. Zhao, Chuan-Lin & Wu, Hai-Juan & Sun, Yang-Qi & Wu, Hao-Qiu & Niu, Dong-Bao, 2024. "A bathtub model with nonlinear velocity–density relation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    12. Nicola Roveri & Antonio Carcaterra & Leonardo Molinari & Gianluca Pepe, 2020. "Safe and Secure Control of Swarms of Vehicles by Small-World Theory," Energies, MDPI, vol. 13(5), pages 1-28, February.
    13. Wang, Shutong & Zhu, Wen-Xing, 2022. "Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    14. Liu, Zhiyong & Li, Ruimin & Wang, Xiaokun(Cara) & Shang, Pan, 2018. "Effects of vehicle restriction policies: Analysis using license plate recognition data in Langfang, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 89-103.
    15. Peng, Guanghan & Li, Xinhai & Wang, Hailing & Tan, Huili, 2024. "Bifurcation and phase transitions in car-following model integrating driver's characteristic and speed limit on spiral slope roads," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    16. Kerner, Boris S., 2021. "Effect of autonomous driving on traffic breakdown in mixed traffic flow: A comparison of classical ACC with three-traffic-phase-ACC (TPACC)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    17. Qin, Yanyan & Liu, Mingxuan & Hao, Wei, 2024. "Energy-optimal car-following model for connected automated vehicles considering traffic flow stability," Energy, Elsevier, vol. 298(C).
    18. Marek Drliciak & Michal Cingel & Jan Celko & Zuzana Panikova, 2024. "Research on Vehicle Congestion Group Identification for Evaluation of Traffic Flow Parameters," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    19. Veronika Harantová & Ambróz Hájnik & Alica Kalašová, 2020. "Comparison of the Flow Rate and Speed of Vehicles on a Representative Road Section before and after the Implementation of Measures in Connection with COVID-19," Sustainability, MDPI, vol. 12(17), pages 1-17, September.
    20. Niaz Mahmud Zafri & Sadia Afroj & Mohammad Ashraf Ali & Md Musleh Uddin Hasan & Md Hamidur Rahman, 2021. "Effectiveness of containment strategies and local cognition to control vehicular traffic volume in Dhaka, Bangladesh during COVID-19 pandemic: Use of Google Map based real-time traffic data," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-16, May.

    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:649:y:2024:i:c:s0378437124004552. 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.