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A new higher-order viscous continuum traffic flow model considering driver memory in the era of autonomous and connected vehicles

Author

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  • Sun, Lu
  • Jafaripournimchahi, Ammar
  • Kornhauser, Alain
  • Hu, Wushen

Abstract

This paper proposes a new car-following model by considering driver memory and derives a corresponding macroscopic continuum traffic flow model, in which the wrong-way travel phenomenon is not going to occur. We reveal that considering driver memory expressed in term of past traffic condition and headway leads to viscosity parameter in macroscopic traffic flow equation. The viscosity parameter is proportional to a unique quantity, which is featured with two parameters: the delay time of vehicle motion and the kinematic wave velocity at jam density. Linear and nonlinear stability analysis using the method of perturbation is carried out to study traffic characteristics. We showed that macroscopic models derived from microscopic models are more realistic and meaningful than those coming directly from an analogy of Navier–Stokes equations.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:547:y:2020:i:c:s0378437119321296
    DOI: 10.1016/j.physa.2019.123829
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    Cited by:

    1. 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).
    2. Hongxia Ge & Siteng Li & Chunyue Yan, 2021. "An Extended Car-Following Model Based on Visual Angle and Electronic Throttle Effect," Mathematics, MDPI, vol. 9(22), pages 1-17, November.
    3. Kang, Yuxiao & Mao, Shuhua & Zhang, Yonghong, 2022. "Fractional time-varying grey traffic flow model based on viscoelastic fluid and its application," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 149-174.
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    5. Zhai, Cong & Wu, Weitiao, 2022. "A continuum model considering the uncertain velocity of preceding vehicles on gradient highways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    6. Jafaripournimchahi, Ammar & Cai, Yingfeng & Wang, Hai & Sun, Lu & Yang, Biao, 2022. "Stability analysis of delayed-feedback control effect in the continuum traffic flow of autonomous vehicles without V2I communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    7. Ammar Jafaripournimchahi & Yingfeng Cai & Hai Wang & Lu Sun, 2022. "Environmental Analyses of Delayed-Feedback Control Effects in Continuum-Traffic Flow of Autonomous Vehicles," Sustainability, MDPI, vol. 14(18), pages 1-18, September.

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