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An improved car-following model with multiple preceding cars’ velocity fluctuation feedback

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Listed:
  • Guo, Lantian
  • Zhao, Xiangmo
  • Yu, Shaowei
  • Li, Xiuhai
  • Shi, Zhongke

Abstract

In order to explore and evaluate the effects of velocity variation trend of multiple preceding cars used in the Cooperative Adaptive Cruise Control (CACC) strategy on the dynamic characteristic, fuel economy and emission of the corresponding traffic flow, we conduct a study as follows: firstly, with the real-time car-following (CF) data, the close relationship between multiple preceding cars’ velocity fluctuation feedback and the host car’s behaviors is explored, the evaluation results clearly show that multiple preceding cars’ velocity fluctuation with different time window-width are highly correlated to the host car’s acceleration/deceleration. Then, a microscopic traffic flow model is proposed to evaluate the effects of multiple preceding cars’ velocity fluctuation feedback in the CACC strategy on the traffic flow evolution process. Finally, numerical simulations on fuel economy and exhaust emission of the traffic flow are also implemented by utilizing VT-micro model. Simulation results prove that considering multiple preceding cars’ velocity fluctuation feedback in the control strategy of the CACC system can improve roadway traffic mobility, fuel economy and exhaust emission performance.

Suggested Citation

  • Guo, Lantian & Zhao, Xiangmo & Yu, Shaowei & Li, Xiuhai & Shi, Zhongke, 2017. "An improved car-following model with multiple preceding cars’ velocity fluctuation feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 436-444.
    • Handle: RePEc:eee:phsmap:v:471:y:2017:i:c:p:436-444
    DOI: 10.1016/j.physa.2016.12.071
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    References listed on IDEAS

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    Cited by:

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    3. 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.
    4. Jin, Zhizhan & Li, Zhipeng & Cheng, Rongjun & Ge, Hongxia, 2018. "Nonlinear analysis for an improved car-following model account for the optimal velocity changes with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 278-288.
    5. Li, Xiangchen & Luo, Xia & He, Mengchen & Chen, Siwei, 2018. "An improved car-following model considering the influence of space gap to the response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 536-545.
    6. Cui, Nan & Chen, Bokui & Zhang, Kai & Zhang, Yi & Liu, Xiaotong & Zhou, Jun, 2019. "Effects of route guidance strategies on traffic emissions in intelligent transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 32-44.
    7. 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.
    8. Tan, Jin-hua, 2019. "Impact of risk illusions on traffic flow in fog weather," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 216-222.
    9. Tang, Yuan & Xue, Yu & Huang, Mu-Yang & Wen, Qi-Yun & Cen, Bing-Ling & Chen, Dong, 2023. "Bifurcation analysis and control strategy for a car-following model considering jerk behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    10. 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).
    11. Cheng, Rongjun & Ge, Hongxia & Sun, Fengxin & Wang, Jufeng, 2018. "An extended macro model accounting for acceleration changes with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 270-283.
    12. Peng, Yong & Liu, Shijie & Yu, Dennis Z., 2020. "An improved car-following model with consideration of multiple preceding and following vehicles in a driver’s view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    13. Jin, Zhizhan & Yang, Zaili & Ge, Hongxia, 2018. "Energy consumption investigation for a new car-following model considering driver’s memory and average speed of the vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1038-1049.
    14. Ding, Heng & Pan, Hao & Bai, Haijian & Zheng, Xiaoyan & Chen, Jin & Zhang, Weihua, 2022. "Driving strategy of connected and autonomous vehicles based on multiple preceding vehicles state estimation in mixed vehicular traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    15. Xiaoyuan Wang & Junyan Han & Chenglin Bai & Huili Shi & Jinglei Zhang & Gang Wang, 2021. "Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment," Future Internet, MDPI, vol. 13(4), pages 1-17, March.

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