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Analysis of a novel lattice hydrodynamic model considering predictive effect and flow integral

Author

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  • Wang, Ting
  • Cheng, Rongjun
  • Ge, Hongxia

Abstract

By taking the predictive effect and flow integral into consideration, we propose an improved lattice hydrodynamic model. Firstly, we apply linear stability analysis to acquire the linear stability condition, which can be used to explain the influence of predictive effect and flow integral on traffic flow stability. After that, the modified Korteweg–de Vries (mKdV) equation is derived through the nonlinear theory, which demonstrates that the solution of mKdV equation can describe traffic jams. Besides, the kink–antikink soliton wave is obtained through solving the mKdV equation, which can describe the propagation characteristics of the traffic density waves. Furthermore, we try to explore how predictive effect and flow integral influence the stability of traffic flow through numerical simulations. Finally, we find that the stability of traffic flow can be efficiently improved with the consideration of the two factors by observing and analyzing the numerical results.

Suggested Citation

  • Wang, Ting & Cheng, Rongjun & Ge, Hongxia, 2019. "Analysis of a novel lattice hydrodynamic model considering predictive effect and flow integral," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119308295
    DOI: 10.1016/j.physa.2019.121425
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    Citations

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    Cited by:

    1. 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).
    2. Kaur, Daljeet & Sharma, Sapna & Gupta, Arvind Kumar, 2022. "Analyses of lattice hydrodynamic area occupancy model for heterogeneous disorder traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    3. Zhai, Cong & Wu, Weitiao & Xiao, Yingping & Luo, Qiang & Zhang, Yusong, 2022. "Modeling bidirectional pedestrian flow with the perceived uncertainty of preceding pedestrian information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    4. Wang, Zihao & Ge, Hongxia & Cheng, Rongjun, 2020. "An extended macro model accounting for the driver’s timid and aggressive attributions and bounded rationality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    5. Li, Wei-Hong & Huang, Hai-Jun & Shang, Hua-Yan, 2020. "Dynamic equilibrium commuting in a multilane system with ridesharing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    6. Zhang, Yicai & Zhao, Min & Sun, Dihua & Liu, Xiaoyu & Huang, Shuai & Chen, Dong, 2022. "Robust H-infinity control for connected vehicles in lattice hydrodynamic model at highway tunnel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    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. 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).
    9. Peng, Guanghan & Jia, Teti & Kuang, Hua & Tan, Huili, 2022. "Energy consumption in a new lattice hydrodynamic model based on the delayed effect of collaborative information transmission under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    10. Zhai, Cong & Wu, Weitiao, 2021. "A continuous traffic flow model considering predictive headway variation and preceding vehicle’s taillight effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).

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