IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v655y2024ics0378437124006836.html
   My bibliography  Save this article

A following model considering multiple vehicles from the driver's front and rear perspectives

Author

Listed:
  • Qi, Weiwei
  • Wang, Wenyi
  • Fu, Chuanyun

Abstract

In the current traffic environment dominated by manual driving, existing models of drivers' rear-view perceptions are inadequate. Existing car-following models that incorporate rear-view information are primarily focused on the Internet of Vehicles (IoV) and automated driving environments. However, they fail to realistically reflect the visual processing mechanisms of human drivers, limiting their effectiveness in realistic traffic scenarios. Therefore, we propose a new following model, the multi-vehicle influence from front and rear perspectives (MVFR), that considers the influence of multiple vehicles. The MVFR model combines information from both front and rear vehicles, integrating views from the front, side front and rear. It provides an in-depth analysis of the effects of relative state differences between a vehicle and its surrounding vehicles on speed, including the effects of perspectives in both the lateral and longitudinal directions. Linear stability analysis and numerical simulation demonstrate that considering the perspectives of rear-following vehicles and lateral offset angles can improve traffic flow stability to a certain extent. Furthermore, properly considering the lateral offset distance and the number of vehicles ahead also positively affects traffic flow stability. This study reveals that observing following vehicles and considering information from multiple front vehicles enhances system stability, especially when there is no or minimal lateral offset. In contrast, focusing on fewer front vehicles is more effective for traffic flow stability when there is a large lateral offset. Experimental results using the CKQ4up dataset show that the MVFR model achieves higher accuracy than the conventional FVD model, the front-view-only improved FVD model (MFVD-RV), and the MFRHVAD-RV and MFRHVAD-AV models. Compared with models relying solely on front-view or non-visual perception, the MVFR model demonstrates a better fit, validating the advantages of this full-view perception model in manual driving environments. This innovation addresses the shortcomings of existing research, thereby enhancing the reliability of models under manual driving conditions on highways.

Suggested Citation

  • Qi, Weiwei & Wang, Wenyi & Fu, Chuanyun, 2024. "A following model considering multiple vehicles from the driver's front and rear perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 655(C).
    • Handle: RePEc:eee:phsmap:v:655:y:2024:i:c:s0378437124006836
    DOI: 10.1016/j.physa.2024.130174
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124006836
    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.2024.130174?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. Sun, Di-Hua & Liao, Xiao-Yong & Peng, Guang-Han, 2011. "Effect of looking backward on traffic flow in an extended multiple car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 631-635.
    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. H. X. Ge & H. B. Zhu & S. Q. Dai, 2006. "Effect of looking backward on traffic flow in a cooperative driving car following model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 54(4), pages 503-507, December.
    4. 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).
    5. Fu, Chuanyun & Lu, Zhaoyou & Ding, Naikan & Bai, Wei, 2024. "Distance headway-based safety evaluation of emerging mixed traffic flow under snowy weather," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 642(C).
    6. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2023. "Jamming transition in two-lane lattice model integrating the deception attacks on influx during the lane-changing process under vehicle to everything environment," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    7. Jiang, Nan & Yu, Bin & Cao, Feng & Dang, Pengfei & Cui, Shaohua, 2021. "An extended visual angle car-following model considering the vehicle types in the adjacent lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    8. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    9. 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).
    10. Peng, Guanghan & Xu, Mingzuo & Tan, Huili, 2024. "Congestion and phase transitions of heterogeneous continuum model with large trucks mixed with conventional vehicles and ACC vehicles," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    11. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2024. "Phase transitions of dual-lane lattice model incorporating cyber-attacks on lane change involving inflow and outflow under connected vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    12. Zheng, Liang & Zhong, Shiquan & Jin, Peter J. & Ma, Shoufeng, 2012. "Influence of lateral discomfort on the stability of traffic flow based on visual angle car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 5948-5959.
    13. Chengjun Kang & Yongsheng Qian & Junwei Zeng & Xuting Wei, 2022. "An improved car-following model considering the preceding vehicle’s velocity feedback and desired inter-vehicle distance," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 33(07), pages 1-19, July.
    14. 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).
    15. Jin, Sheng & Wang, Dian-Hai & Huang, Zhi-Yi & Tao, Peng-Fei, 2011. "Visual angle model for car-following theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 1931-1940.
    16. Wang, Xiaoning & Liu, Minzhuang & Ci, Yusheng & Wu, Lina, 2022. "Effect of front two adjacent vehicles’ velocity information on car-following model construction and stability analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(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. Tian, Chuan & Kang, Yirong, 2025. "Modeling and optimal congestion control of multi-lane highway traffic with on-ramp and off-ramp under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 661(C).
    2. Verma, Muskan & Gupta, Arvind Kumar & Sharma, Sapna, 2025. "Phase transitions in a multi-phase lattice hydrodynamic area occupancy model in mixed disorder traffic considering connected and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 658(C).
    3. Wu, Xinyu & Xiao, Xinping, 2024. "An improved stochastic car-following model considering the complete state information of multiple preceding vehicles under connected vehicles environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 644(C).
    4. Yin, Yu-Hang & Lü, Xing & Jiang, Rui & Jia, Bin & Gao, Ziyou, 2024. "Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in ITS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    5. Yadav, Darshana & Siwach, Vikash & Redhu, Poonam, 2025. "The interplay of passing, driver attention, and cyber attack-induced information delays on traffic stability," Chaos, Solitons & Fractals, Elsevier, vol. 196(C).
    6. Zhai, Cong & Wu, Weitiao & Zhang, Jiyong & Xiao, Yingping & Zhai, Min, 2024. "An anisotropic macroscopic mixed-flow model integrating the perceptual domains differences impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    7. 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).
    8. Jin, Can & Qing, Li & Zhu, Meilan & Peng, Guanghan, 2025. "Phase transitions and spectral entropy of heterogeneous vehicles comprised of CAVs and HDVs in flux restriction scenarios," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    9. Peng, Guanghan & Zhu, Meilan & Tan, Huili, 2024. "Jams and phase transitions in heterogeneous lattice model integrating the continuous delayed feedback control to boycott cyber-attacks under connected autonomous and human driven vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
    10. 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).
    11. Wang, Zihao & Ge, Hongxia & Cheng, Rongjun, 2018. "Nonlinear analysis for a modified continuum model considering driver’s memory and backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 18-27.
    12. Li, Linheng & An, Bocheng & Wang, Zhiyu & Gan, Jing & Qu, Xu & Ran, Bin, 2024. "Stability analysis and numerical simulation of a car-following model considering safety potential field and V2X communication: A focus on influence weight of multiple vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    13. Zhang, Geng & Guo, Hai-Yan & Ren, Yue & Gan, Hao-Ting, 2025. "Stability and phase transition of a novel lattice hydrodynamic model considering different flux information coordination methods," Chaos, Solitons & Fractals, Elsevier, vol. 196(C).
    14. Zhang, Xingrong & Cai, Jiaxuan & Chen, Fuzhou & Cheng, Rongjun, 2024. "Multimodal vehicle trajectory prediction and integrated threat assessment algorithm based on adaptive driving intention," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    15. Peng, Guanghan & Xu, Mingzuo & Tan, Huili, 2024. "Congestion and phase transitions of heterogeneous continuum model with large trucks mixed with conventional vehicles and ACC vehicles," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    16. Chen, Yujiao & Zhang, Futao & Qian, Yongsheng & Zeng, Junwei & Li, Xin, 2025. "A new car-following model considering the driver's dynamic reaction time and driving visual angle on the slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 663(C).
    17. Jin, Can & Peng, Guanghan & Huang, Yixin, 2025. "Phase transitions in operation of heterogeneous vehicles mixed with human-driven and connected autonomous vehicles under speed restriction circumstances," Chaos, Solitons & Fractals, Elsevier, vol. 195(C).
    18. Cheng-Ju Song & Hong-Fei Jia, 2022. "Car-Following Model Optimization and Simulation Based on Cooperative Adaptive Cruise Control," Sustainability, MDPI, vol. 14(21), pages 1-12, October.
    19. Maiti, Nandan & Chilukuri, Bhargava Rama, 2023. "Does anisotropy hold in mixed traffic conditions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    20. Jiang, Nan & Yu, Bin & Cao, Feng & Dang, Pengfei & Cui, Shaohua, 2021. "An extended visual angle car-following model considering the vehicle types in the adjacent lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(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:655:y:2024:i:c:s0378437124006836. 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.