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Car-following model for autonomous vehicles and mixed traffic flow analysis based on discrete following interval

Author

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  • An, Shuke
  • Xu, Liangjie
  • Qian, Lianghui
  • Chen, Guojun
  • Luo, Haoshun
  • Li, Fu

Abstract

In this paper, a discrete car-following interval model for autonomous vehicles is proposed, with the steady following and dynamic following intervals, and the range of the steady following interval is established. The stability conditions of the model are explored using linear stability analysis theory. Numerical simulation is used to verify the influence of the discrete following interval model on mixed traffic flow under small perturbations and hard braking. The research results show that with the increase in the proportion of autonomous vehicles, the stability of traffic flow is gradually enhanced. In particular, in the small perturbation condition, the autonomous vehicle has a speed maintenance period in the steady following interval, thereby reducing the influence of the preceding vehicle perturbations. With the increase of the steady following interval, the stability of traffic flow first increases and then decreases. Moreover, when the length of steady following interval is constant, with the increase of the minimum safety time headway, the stability of traffic flow is gradually enhanced.

Suggested Citation

  • An, Shuke & Xu, Liangjie & Qian, Lianghui & Chen, Guojun & Luo, Haoshun & Li, Fu, 2020. "Car-following model for autonomous vehicles and mixed traffic flow analysis based on discrete following interval," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
  • Handle: RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120306580
    DOI: 10.1016/j.physa.2020.125246
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    Citations

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    Cited by:

    1. Li, Jing & Liu, Di & Baldi, Simone, 2024. "Modular nudging models: Formulation and identification from real-world traffic data sets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    2. Hossain, Md. Anowar & Tanimoto, Jun, 2022. "A microscopic traffic flow model for sharing information from a vehicle to vehicle by considering system time delay effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Toan, Trinh Dinh & Lam, Soi Hoi & Wong, Yiik Diew & Meng, Meng, 2022. "Development and validation of a driving simulator for traffic control using field data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    4. Huang, Wei & Hu, Yang, 2022. "A modified cell transmission model considering queuing characteristics for channelized zone at signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    5. Huimin Liu & Rongjun Cheng & Tingliu Xu, 2021. "Analysis of a Novel Two-Dimensional Lattice Hydrodynamic Model Considering Predictive Effect," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    6. Huanping Li & Jian Wang & Guopeng Bai & Xiaowei Hu, 2021. "Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads," Energies, MDPI, vol. 14(12), pages 1-21, June.
    7. Chengju Song & Hongfei Jia, 2022. "Multi-State Car-Following Behavior Simulation in a Mixed Traffic Flow for ICVs and MDVs," Sustainability, MDPI, vol. 14(20), pages 1-12, October.
    8. Zhang, Qianran & Ma, Shoufeng & Tian, Junfang & Rose, John M. & Jia, Ning, 2022. "Mode choice between autonomous vehicles and manually-driven vehicles: An experimental study of information and reward," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 24-39.
    9. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    10. 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).
    11. 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.
    12. Wang, Shutong & Zhu, Wen-Xing, 2022. "Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    13. Bari, Chintaman Santosh & Chandra, Satish & Dhamaniya, Ashish, 2022. "Service headway distribution analysis of FASTag lanes under mixed traffic conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    14. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2024. "Phase transitions of dual-lane lattice model incorporating cyber-attacks on lane change involving inflow and outflow under connected vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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