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V2I-based car-following modeling and simulation of signalized intersection

Author

Listed:
  • Ci, Yusheng
  • Wu, Lina
  • Zhao, Jiafa
  • Sun, Yichen
  • Zhang, Guohui

Abstract

In order to study the influence of V2I (Vehicle-To-Infrastructure) on traffic flow at signalized intersections, a vehicle-following model at signalized intersections based on V2I is established in this paper. On the basis of the FVD (Full Velocity Difference) model, the influence of V2I on the operation of intelligent vehicles at signalized intersections is considered. Through the numerical simulation analysis, it was found that the vehicle following model based on the V2I signalized intersection can better reflect the effect of V2I on the vehicle operation at the intersection. At the same time, with the increase of the influence degree and range of V2I, it can effectively improve the traffic efficiency of the vehicles at the signalized intersection.

Suggested Citation

  • Ci, Yusheng & Wu, Lina & Zhao, Jiafa & Sun, Yichen & Zhang, Guohui, 2019. "V2I-based car-following modeling and simulation of signalized intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 672-679.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:672-679
    DOI: 10.1016/j.physa.2019.03.062
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Junyan Han & Xiaoyuan Wang & Huili Shi & Bin Wang & Gang Wang & Longfei Chen & Quanzheng Wang, 2022. "Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    2. Shuaiyang Jiao & Shengrui Zhang & Bei Zhou & Zixuan Zhang & Liyuan Xue, 2020. "An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    3. Cui, Ziyu & Wang, Xiaoning & Ci, Yusheng & Yang, Changyun & Yao, Jia, 2023. "Modeling and analysis of car-following models incorporating multiple lead vehicles and acceleration information in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Yongyi Li & Wei Yang & Xiaorui Zhang & Xi Kang & Mengfei Li, 2022. "Research on Automatic Driving Trajectory Planning and Tracking Control Based on Improvement of the Artificial Potential Field Method," Sustainability, MDPI, vol. 14(19), pages 1-28, September.
    5. Cheng-Ju Song & Hong-Fei Jia, 2022. "Car-Following Model Optimization and Simulation Based on Cooperative Adaptive Cruise Control," Sustainability, MDPI, vol. 14(21), pages 1-12, October.
    6. 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).
    7. Wang, Tao & Yuan, Zijian & Zhang, Yuanshu & Zhang, Jing & Tian, Junfang, 2023. "A driving guidance strategy with pre-stop line at signalized intersection: Collaborative optimization of capacity and fuel consumption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    8. Manivasakan, Hesavar & Kalra, Riddhi & O'Hern, Steve & Fang, Yihai & Xi, Yinfei & Zheng, Nan, 2021. "Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 36-53.

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