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Impact of the traffic interruption probability of optimal current on traffic congestion in lattice model

Author

Listed:
  • Peng, Guanghan
  • Lu, Weizhen
  • He, Hongdi

Abstract

In this paper, a new lattice model is proposed with the consideration of the traffic interruption probability of the optimal current. The linear stability condition is obtained by linear stability analysis and the mKdV equation is deducted from nonlinear analysis via considering the traffic interruption probability of the optimal current, respectively. The results of numerical simulation show that the traffic interruption probability of the optimal current can efficiently suppress traffic jams under high response coefficient and deteriorate traffic situations under low response coefficient.

Suggested Citation

  • Peng, Guanghan & Lu, Weizhen & He, Hongdi, 2015. "Impact of the traffic interruption probability of optimal current on traffic congestion in lattice model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 27-33.
    • Handle: RePEc:eee:phsmap:v:425:y:2015:i:c:p:27-33
    DOI: 10.1016/j.physa.2015.01.045
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    Citations

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    Cited by:

    1. Wang, Jufeng & Sun, Fengxin & Ge, Hongxia, 2018. "Effect of the driver’s desire for smooth driving on the car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 96-108.
    2. Yongjiang-Wang, & Han-Song, & Rongjun-Cheng,, 2019. "TDGL and mKdV equations for an extended car-following model with the consideration of driver’s memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 440-449.
    3. Sun, Fengxin & Wang, Jufeng & Cheng, Rongjun, 2019. "An improved anisotropic continuum model considering the driver’s desire for steady driving," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1449-1462.
    4. Leng, Jun-Qiang & Liu, Wei-Yi & Zhao, Lin, 2017. "Analysis of electric vehicle’s trip cost allowing late arrival," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 293-300.
    5. Wang, Jufeng & Sun, Fengxin & Ge, Hongxia, 2019. "An improved lattice hydrodynamic model considering the driver’s desire of driving smoothly," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 119-129.
    6. Qi, Xinyue & Ge, Hongxia & Cheng, Rongjun, 2019. "Analysis of a novel lattice hydrodynamic model considering density integral and “backward looking” effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 714-723.
    7. Hou, Qinzhong & Meng, Xianghai & Leng, Junqiang & Yu, Lu, 2018. "Application of a random effects negative binomial model to examine crash frequency for freeways in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 937-944.
    8. Hou, Qinzhong & Meng, Xianghai & Huo, Xiaoyan & Cheng, Yuxing & Leng, Junqiang, 2019. "Effects of freeway climbing lane on crash frequency: Application of propensity scores and potential outcomes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 246-256.
    9. Leng, Jun-Qiang & Zhao, Lin, 2017. "Analysis of electric vehicle’s trip cost without late arrival," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 761-766.
    10. Wang, Qingying & Ge, Hongxia, 2019. "An improved lattice hydrodynamic model accounting for the effect of “backward looking” and flow integral," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 438-446.
    11. Jiang, Changtao & Cheng, Rongjun & Ge, Hongxia, 2018. "Effects of speed deviation and density difference in traffic lattice hydrodynamic model with interruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 900-908.

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