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Integrating the historical evolution information integral effect in car-following model under the V2X environment

Author

Listed:
  • Peng, Guanghan
  • Jia, Teti
  • Zhao, Hongzhuan
  • Tan, Huili

Abstract

The historical evolution information integral (HEII) effect has a significant impact on drivers’ subsequent traffic behavior. At present, The HEII effect can be conveyed by means of vehicle-to-X (V2X) communication technology for connected vehicles, which contributes to improving traffic safety, restraining traffic congestion and lessening pollution emissions. Then, based on the cooperative transmission of HEII effect under the V2X environment, a novel car-following model is brought up. Through linear analysis and nonlinear analysis, the neutral stability curve and mKdV equation are inferred. Theoretical analysis and numerical simulation results certify that the cooperative transmission of the HEII effect can prominently suppress traffic congestion according to headway, acceleration and hysteresis phenomena. More importantly, the HEII effect cuts down CO2 emission effectively.

Suggested Citation

  • Peng, Guanghan & Jia, Teti & Zhao, Hongzhuan & Tan, Huili, 2023. "Integrating the historical evolution information integral effect in car-following model under the V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    • Handle: RePEc:eee:phsmap:v:627:y:2023:i:c:s0378437123006805
    DOI: 10.1016/j.physa.2023.129125
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    Citations

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    Cited by:

    1. 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).
    2. Yadav, Sunita & Redhu, Poonam, 2024. "Impact of driving prediction on headway and velocity in car-following model under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    3. 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).
    4. 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).
    5. Kang, Chengjun & Qian, Yongsheng & Zeng, Junwei & Wei, Xuting & Zhang, Futao, 2024. "Analysis of stability, energy consumption and CO2 emissions in novel discrete-time car-following model with time delay under V2V environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    6. 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).
    7. Zhang, Jing & Gao, Qian & Tian, Junfang & Cui, Fengying & Wang, Tao, 2024. "Car-following model based on spatial expectation effect in connected vehicle environment: modeling, stability analysis and identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    8. Ma, Guangyi & Li, Keping, 2024. "Analysis and simulation of vehicle following behavior with consideration of multiple time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).

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