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Two velocity difference model for a car following theory

Author

Listed:
  • Ge, H.X.
  • Cheng, R.J.
  • Li, Z.P.

Abstract

In the light of the optimal velocity model, a two velocity difference model for a car-following theory is put forward considering navigation in modern traffic. To our knowledge, the model is an improvement over the previous ones theoretically, because it considers more aspects in the car-following process than others. Then we investigate the property of the model using linear and nonlinear analyses. The Korteweg–de Vries equation (for short, the KdV equation) near the neutral stability line and the modified Korteweg–de Vries equation (for short, the mKdV equation) around the critical point are derived by applying the reductive perturbation method. The traffic jam could be thus described by the KdV soliton and the kink–anti-kink soliton for the KdV equation and mKdV equation, respectively. Numerical simulations are made to verify the model, and good results are obtained with the new model.

Suggested Citation

  • Ge, H.X. & Cheng, R.J. & Li, Z.P., 2008. "Two velocity difference model for a car following theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5239-5245.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5239-5245
    DOI: 10.1016/j.physa.2008.02.081
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    Citations

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    Cited by:

    1. Zhu, Chenqiang & Zhong, Shiquan & Li, Guangyu & Ma, Shoufeng, 2017. "New control strategy for the lattice hydrodynamic model of traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 445-453.
    2. Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2018. "An extended car-following model under V2V communication environment and its delayed-feedback control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 349-358.
    3. Jin, Zhizhan & Li, Zhipeng & Cheng, Rongjun & Ge, Hongxia, 2018. "Nonlinear analysis for an improved car-following model account for the optimal velocity changes with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 278-288.
    4. Qin, Shunda & He, Zhiting & Cheng, Rongjun, 2018. "An extended lattice hydrodynamic model based on control theory considering the memory effect of flux difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 809-816.
    5. Chen, Can & Cheng, Rongjun & Ge, Hongxia, 2019. "An extended car-following model considering driver’s sensory memory and the backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 278-289.
    6. Wen Huan Ai & Ming Ming Wang & Da Wei Liu, 2023. "Analysis of macroscopic traffic flow model considering throttle dynamics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-18, June.
    7. Li, Shihao & Cheng, Rongjun & Ge, Hongxia, 2020. "An improved car-following model considering electronic throttle dynamics and delayed velocity difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    8. Liu, Fangxun & Cheng, Rongjun & Ge, Hongxia & Yu, Chenyan, 2016. "A new car-following model with consideration of the velocity difference between the current speed and the historical speed of the leading car," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 267-277.
    9. Sun, Lu & Jafaripournimchahi, Ammar & Kornhauser, Alain & Hu, Wushen, 2020. "A new higher-order viscous continuum traffic flow model considering driver memory in the era of autonomous and connected vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    10. Yu, Shaowei & Huang, Mengxing & Ren, Jia & Shi, Zhongke, 2016. "An improved car-following model considering velocity fluctuation of the immediately ahead car," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 1-17.
    11. Cheng, Rongjun & Ge, Hongxia & Sun, Fengxin & Wang, Jufeng, 2018. "An extended macro model accounting for acceleration changes with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 270-283.
    12. He, Jia & Huang, Hai-Jun & Yang, Hai & Tang, Tie-Qiao, 2017. "An electric vehicle driving behavior model in the traffic system with a wireless charging lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 119-126.
    13. Mei, Yiru & Zhao, Xiaoqun & Qian, Yeqing & Xu, Shangzhi & Li, Zhipeng, 2021. "Effect of self-stabilizing control in lattice hydrodynamic model with on-ramp and off-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    14. Jin, Zhizhan & Yang, Zaili & Ge, Hongxia, 2018. "Energy consumption investigation for a new car-following model considering driver’s memory and average speed of the vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1038-1049.
    15. 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).

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