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The effect of Headway Variation Tendency on traffic flow: Modeling and stabilization

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  • Wang, Tao
  • Li, Guangyao
  • Zhang, Jing
  • Li, Shubin
  • Sun, Tao

Abstract

Advanced communications technology enables us to obtain the Headway Variation Tendency (HVT) of the next moment in a car following scenario. To maximize the benefits of the new technology, we developed a new traffic flow model that takes into consideration the effect of HVT. First, linear analysis method is used to derive the linear stability condition, that determines whether the HVT can improve traffic system stability. Then, using the reductive perturbation method, a modified KdV (mKdV) equation is obtained and the kink–antikink solutions are derived. The phase diagram of driver sensitivity against equilibrium headway is also plotted by using the neutral stability line, derived from linear analysis and the coexisting line, derived from nonlinear analysis. This diagram demonstrates that HVT does have the ability to improve the stability of traffic stream. Finally, the effect of HVT is validated through numerical simulations, where it is evident that the information of HVT can smooth the traffic stream and prevent the formation of traffic congestion.

Suggested Citation

  • Wang, Tao & Li, Guangyao & Zhang, Jing & Li, Shubin & Sun, Tao, 2019. "The effect of Headway Variation Tendency on traffic flow: Modeling and stabilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 566-575.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:566-575
    DOI: 10.1016/j.physa.2019.03.116
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    Cited by:

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    2. Sun, Lu & Jafaripournimchahi, Ammar & Hu, Wusheng, 2020. "A forward-looking anticipative viscous high-order continuum model considering two leading vehicles for traffic flow through wireless V2X communication in autonomous and connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    3. Zhang, Jing & Wang, Bo & Li, Shubin & Sun, Tao & Wang, Tao, 2020. "Modeling and application analysis of car-following model with predictive headway variation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. Zhang, Jing & Xu, Keyu & Li, Guangyao & Li, Shubin & Wang, Tao, 2021. "Dynamics of traffic flow affected by the future motion of multiple preceding vehicles under vehicle-connected environment: Modeling and stabilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    5. Zhang, Jing & Xu, Keyu & Li, Shubin & Wang, Tao, 2020. "A new two-lane lattice hydrodynamic model with the introduction of driver’s predictive effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    6. 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).
    7. 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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