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Visual angle model for car-following theory

Author

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  • Jin, Sheng
  • Wang, Dian-Hai
  • Huang, Zhi-Yi
  • Tao, Peng-Fei

Abstract

The vast majority of car-following models are lack of the consideration of human drivers’ characteristics. Based on the fact that each driver of a following vehicle perceives closing-in or shying-away a leading vehicle in front of him/her, primarily due to changes in the apparent size of the leading vehicle, we improved the full velocity difference (FVD) model and presented a visual angle car-following model. This model is in view of the stimulus–response framework and uses the visual angle and the change rate of the visual angle as stimulus. Results from linear analysis showed that the neutral stability line is asymmetry and the width of the leading vehicle has a great impact on the stability of traffic flow. Numerical simulations obtained the same results as theoretical analysis clearly such as density wave, shrinking hysteresis, asymmetry and wide scattering. Thus, the introducing of the visual angle can explain some complex nature of traffic flow and contribute to the design of more realistic car-following models.

Suggested Citation

  • Jin, Sheng & Wang, Dian-Hai & Huang, Zhi-Yi & Tao, Peng-Fei, 2011. "Visual angle model for car-following theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 1931-1940.
  • Handle: RePEc:eee:phsmap:v:390:y:2011:i:11:p:1931-1940
    DOI: 10.1016/j.physa.2011.01.012
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    Citations

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    Cited by:

    1. 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.
    2. Yang, Da & Jin, Peter (Jing) & Pu, Yun & Ran, Bin, 2014. "Stability analysis of the mixed traffic flow of cars and trucks using heterogeneous optimal velocity car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 371-383.
    3. 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.
    4. 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).
    5. 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.
    6. Jiang, Nan & Yu, Bin & Cao, Feng & Dang, Pengfei & Cui, Shaohua, 2021. "An extended visual angle car-following model considering the vehicle types in the adjacent lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    7. Dong-Min Son & Hyuk-Ju Kwon & Sung-Hak Lee, 2023. "Enhanced Night-to-Day Image Conversion Using CycleGAN-Based Base-Detail Paired Training," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    8. 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.
    9. Zhang, Xiangzhou & Shi, Zhongke & Yu, Shaowei & Ma, Lijing, 2023. "A new car-following model considering driver’s desired visual angle on sharp curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    10. Jin, Sheng & Qu, Xiaobo & Zhou, Dan & Xu, Cheng & Ma, Dongfang & Wang, Dianhai, 2015. "Estimating cycleway capacity and bicycle equivalent unit for electric bicycles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 225-248.
    11. Maosheng Li & Jing Fan & Jaeyoung Lee, 2023. "Modeling Car-Following Behavior with Different Acceptable Safety Levels," Sustainability, MDPI, vol. 15(7), pages 1-23, April.
    12. Ponnu, Balaji & Coifman, Benjamin, 2015. "Speed-spacing dependency on relative speed from the adjacent lane: New insights for car following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 74-90.
    13. Guan, Xueyi & Cheng, Rongjun & Ge, Hongxia, 2021. "Bifurcation control of optimal velocity model through anticipated effect and response time-delay feedback methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    14. Li, Xin & Li, Xingang & Xiao, Yao & Jia, Bin, 2016. "Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 49-62.
    15. Muhammad Tanveer & Faizan Ahmad Kashmiri & Hassan Naeem & Huimin Yan & Xin Qi & Syed Muzammil Abbas Rizvi & Tianshi Wang & Huapu Lu, 2020. "An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach," Sustainability, MDPI, vol. 12(7), pages 1-22, April.

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