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Research on multiple vehicles’ continuous self-delayed velocities on traffic flow with vehicle-to-vehicle communication

Author

Listed:
  • Zhang, Geng
  • Yin, Le
  • Pan, Dong-Bo
  • Zhang, Yu
  • Cui, Bo-Yuan
  • Jiang, Shan

Abstract

Under the vehicle-to-vehicle communication environment, different kinds and different ranges of traffic information could be obtained and used for the coordinated operation of road traffic system. To reveal the influence of multiple preceding vehicles’ continuous self-delayed velocities information on traffic flow, an extended car-following model by considering multiple preceding vehicles’ continuous self-delayed velocities is put forward. Further, the performance of the new model is studied by linear and nonlinear analyses, and also by simulation experiment. The results show that multiple preceding vehicles’ continuous self-delayed velocities information affects the stability of traffic flow importantly.

Suggested Citation

  • Zhang, Geng & Yin, Le & Pan, Dong-Bo & Zhang, Yu & Cui, Bo-Yuan & Jiang, Shan, 2020. "Research on multiple vehicles’ continuous self-delayed velocities on traffic flow with vehicle-to-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    • Handle: RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119320631
    DOI: 10.1016/j.physa.2019.123704
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    References listed on IDEAS

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    1. Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "An extended car-following model considering driver’s desire for smooth driving on the curved road," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    2. Yu, Shaowei & Shi, Zhongke, 2014. "An extended car-following model at signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 152-159.
    3. Yang, Liang-Yi & Sun, Di-Hua & Zhao, Min & Cheng, Sen-Lin & Zhang, Geng & Liu, Hui, 2018. "The influence of continuous historical velocity difference information on micro-cooperative driving stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 294-301.
    4. Zhang, Geng & Sun, Di-Hua & Zhao, Min & Liao, Xiao-Yong & Liu, Wei-Ning & Zhou, Tong, 2018. "An extended car-following model accounting for cooperation driving system with velocity uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1008-1017.
    5. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    6. Gao, Shigen & Dong, Hairong & Song, Haifeng & Zhou, Min, 2019. "On state feedback control and Lyapunov analysis of car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    7. Liu, Lan & Zhu, Liling & Yang, Da, 2016. "Modeling and simulation of the car-truck heterogeneous traffic flow based on a nonlinear car-following model," Applied Mathematics and Computation, Elsevier, vol. 273(C), pages 706-717.
    8. Peng, Guanghan & Yang, Shuhong & Xia, Dongxue & Li, Xiaoqin, 2019. "Delayed-feedback control in a car-following model with the combination of V2V communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    9. Zhang, Geng & Zhang, Yu & Pan, Dong-bo & Sang, Chun-yan, 2019. "Study on the interval integration effect of vehicle’s self-delayed velocity on traffic stability in micro traffic modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    10. Tang, Tie-Qiao & Li, Jin-Gang & Yang, Shi-Chun & Shang, Hua-Yan, 2015. "Effects of on-ramp on the fuel consumption of the vehicles on the main road under car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 293-300.
    11. Cao, Bao-gui, 2015. "A new car-following model considering driver’s sensory memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 218-225.
    12. Sun, Jie & Zheng, Zuduo & Sun, Jian, 2018. "Stability analysis methods and their applicability to car-following models in conventional and connected environments," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 212-237.
    13. Zhao, Jing & Li, Peng, 2017. "An extended car-following model with consideration of vehicle to vehicle communication of two conflicting streams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 178-187.
    14. Malenje, Jairus Odawa & Zhao, Jing & Li, Peng & Han, Yin, 2018. "An extended car-following model with the consideration of the illegal pedestrian crossing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 650-661.
    15. Zhu, Wen-Xing & Zhang, H.M., 2018. "Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 274-285.
    16. Zhou, Yang & Wang, Meng & Ahn, Soyoung, 2019. "Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 69-86.
    17. Wang, Pengcheng & Yu, Guizhen & Wu, Xinkai & Qin, Hongmao & Wang, Yunpeng, 2018. "An extended car-following model to describe connected traffic dynamics under cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 351-370.
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    Cited by:

    1. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2023. "Jamming transition in two-lane lattice model integrating the deception attacks on influx during the lane-changing process under vehicle to everything environment," Chaos, Solitons & Fractals, Elsevier, vol. 176(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. Wang, Xiaoning & Liu, Minzhuang & Ci, Yusheng & Wu, Lina, 2022. "Effect of front two adjacent vehicles’ velocity information on car-following model construction and stability analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Junyan Han & Jinglei Zhang & Xiaoyuan Wang & Yaqi Liu & Quanzheng Wang & Fusheng Zhong, 2020. "An Extended Car-Following Model Considering Generalized Preceding Vehicles in V2X Environment," Future Internet, MDPI, vol. 12(12), pages 1-15, November.

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