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An improved car-following model considering headway changes with memory

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  • Yu, Shaowei
  • Shi, Zhongke

Abstract

To describe car-following behaviors in complex situations better, increase roadway traffic mobility and minimize cars’ fuel consumptions, the linkage between headway changes with memory and car-following behaviors was explored with the field car-following data by using the gray correlation analysis method, and then an improved car-following model considering headway changes with memory on a single lane was proposed based on the full velocity difference model. Some numerical simulations were carried out by employing the improved car-following model to explore how headway changes with memory affected each car’s velocity, acceleration, headway and fuel consumptions. The research results show that headway changes with memory have significant effects on car-following behaviors and fuel consumptions and that considering headway changes with memory in designing the adaptive cruise control strategy can improve the traffic flow stability and minimize cars’ fuel consumptions.

Suggested Citation

  • Yu, Shaowei & Shi, Zhongke, 2015. "An improved car-following model considering headway changes with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 1-14.
    • Handle: RePEc:eee:phsmap:v:421:y:2015:i:c:p:1-14
    DOI: 10.1016/j.physa.2014.11.008
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    Citations

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    Cited by:

    1. Liao, Peng & Tang, Tie-Qiao & Wang, Tao & Zhang, Jian, 2019. "A car-following model accounting for the driving habits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 108-118.
    2. Jaimie McNabb & Rob Gray, 2016. "Staying Connected on the Road: A Comparison of Different Types of Smart Phone Use in a Driving Simulator," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-12, February.
    3. Xin, Qi & Yang, Nan & Fu, Rui & Yu, Shaowei & Shi, Zhongke, 2018. "Impacts analysis of car following models considering variable vehicular gap policies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 338-355.
    4. Hongxing Zhao & Ruichun He & Xiaoyan Jia, 2019. "Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model," Sustainability, MDPI, vol. 11(14), pages 1-25, July.
    5. Wang, Jufeng & Sun, Fengxin & Cheng, Rongjun & Ge, Hongxia, 2018. "An extended heterogeneous car-following model with the consideration of the drivers’ different psychological headways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1113-1125.
    6. Pei, Xin & Pan, Yan & Wang, Haixin & Wong, S.C. & Choi, Keechoo, 2016. "Empirical evidence and stability analysis of the linear car-following model with gamma-distributed memory effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 311-323.
    7. Xiaomeng Wang & Ling Peng & Tianhe Chi & Mengzhu Li & Xiaojing Yao & Jing Shao, 2015. "A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-20, December.
    8. Li, Yongfu & Kang, Yuhao & Yang, Bin & Peeta, Srinivas & Zhang, Li & Zheng, Taixong & Li, Yinguo, 2016. "A sliding mode controller for vehicular traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 38-47.
    9. Liu, Yi & Cheng, Rong-jun & Lei, Li & Ge, Hong-xia, 2016. "The influence of the non-motor vehicles for the car-following model considering traffic jerk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 376-382.
    10. Ma, Guangyi & Ma, Minghui & Liang, Shidong & Wang, Yansong & Guo, Hui, 2021. "Nonlinear analysis of the car-following model considering headway changes with memory and backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    11. 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.
    12. Zhang, Xiangzhou & Shi, Zhongke & Chen, Jianzhong & Ma, lijing, 2023. "A bi-directional visual angle car-following model considering collision sensitivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    13. Yu, Shaowei & Huang, Mengxing & Ren, Jia & Shi, Zhongke, 2016. "An improved car-following model considering velocity fluctuation of the immediately ahead car," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 1-17.
    14. 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.
    15. He, Jia & He, Zhengbing & Fan, Bo & Chen, Yanyan, 2020. "Optimal location of lane-changing warning point in a two-lane road considering different traffic flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    16. Weiqi Zhou & Nanchi Wu & Qingchao Liu & Chaofeng Pan & Long Chen, 2023. "Research on Ecological Driving Following Strategy Based on Deep Reinforcement Learning," Sustainability, MDPI, vol. 15(18), pages 1-14, September.
    17. Qingtao, Zhai & Hongxia, Ge & Rongjun, Cheng, 2018. "An extended continuum model considering optimal velocity change with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 774-785.

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