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An improved car-following model with consideration of multiple preceding and following vehicles in a driver’s view

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  • Peng, Yong
  • Liu, Shijie
  • Yu, Dennis Z.

Abstract

Common driving experience suggests that a driver’s car-following behavior is often affected by the preceding and following vehicles in the driver’s view. In this study, we propose an improved car-following model based on the full velocity difference (FVD) model by considering two preceding and the immediate following vehicles in a driver’s view. Car-following data extracted from real traffic situation is used to calibrate and verify both of the improved model and the FVD model. Our data analysis shows that the motion status of two preceding vehicles and one following vehicle in a driver’s view can influence traffic flow of following vehicles after the driver’s vehicle. We compare the performance of the improved model and the FVD model by simulating the starting and braking processes of the following vehicles. The numerical simulation study shows that the improved model fits the experimental data better than the FVD model by showing a shorter time of completing the starting and braking processes of the following vehicles.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:538:y:2020:i:c:s0378437119316796
    DOI: 10.1016/j.physa.2019.122967
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    References listed on IDEAS

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    Cited by:

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    2. Lou, Haoli & Lyu, Hao & Cheng, Rongjun, 2024. "A time-varying driving style oriented model predictive control for smoothing mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
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    4. Ting, Samson & Lymburn, Thomas & Stemler, Thomas & Sun, Yuchao & Small, Michael, 2024. "Parameter estimation for Gipps’ car following model in a Bayesian framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    5. 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).
    6. 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.
    7. Yi, Ziwei & Lu, Wenqi & Qu, Xu & Gan, Jing & Li, Linheng & Ran, Bin, 2022. "A bidirectional car-following model considering distance balance between adjacent vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    8. 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.

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