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An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment

Author

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  • Shuaiyang Jiao

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Shengrui Zhang

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Bei Zhou

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Zixuan Zhang

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Liyuan Xue

    (School of Civil and Transportation Engineering, Henan University of Urban Construction, Pingdingshan 467036, China)

Abstract

In intelligent transportation systems, vehicles can obtain more information, and the interactivity between vehicles can be improved. Therefore, it is necessary to study car-following behavior during the introduction of intelligent traffic information technology. To study the impacts of drivers’ characteristics on the dynamic characteristics of car-following behavior in a vehicle-to-vehicle (V2V) communication environment, we first analyzed the relationship between drivers’ characteristics and the following car’s optimal velocity using vehicle trajectory data via the grey relational analysis method and then presented a new optimal velocity function (OVF). The boundary conditions of the new OVF were analyzed theoretically, and the results showed that the new OVF can better describe drivers’ characteristics than the traditional OVF. Subsequently, we proposed an extended car-following model by combining V2V communication based on the new OVF and previous car-following models. Finally, numerical simulations were carried out to explore the effect of drivers’ characteristics on car-following behavior and fuel economy of vehicles, and the results indicated that the proposed model can improve vehicles’ mobility, safety, fuel consumption, and emissions in different traffic scenarios. In conclusion, the performance of traffic flow was improved by taking drivers’ characteristics into account under the V2V communication situation for car-following theory.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1552-:d:322413
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    References listed on IDEAS

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    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. Tian, Junfang & Zhang, H.M. & Treiber, Martin & Jiang, Rui & Gao, Zi-You & Jia, Bin, 2019. "On the role of speed adaptation and spacing indifference in traffic instability: Evidence from car-following experiments and its stochastic model," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 334-350.
    3. 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.
    4. He, Zhengbing & Zheng, Liang & Guan, Wei, 2015. "A simple nonparametric car-following model driven by field data," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 185-201.
    5. Gong, Huaxin & Liu, Hongchao & Wang, Bing-Hong, 2008. "An asymmetric full velocity difference car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2595-2602.
    6. Klawtanong, Manit & Limkumnerd, Surachate, 2020. "Dissipation of traffic congestion using autonomous-based car-following model with modified optimal velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    7. Zhang, Jian & Tang, Tie-Qiao & Yu, Shao-Wei, 2018. "An improved car-following model accounting for the preceding car’s taillight," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1831-1837.
    8. 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.
    9. Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "An extended car-following model considering driver’s memory and average speed of preceding vehicles with control strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 752-761.
    10. 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).
    11. Kayvan Aghabayk & Majid Sarvi & William Young, 2015. "A State-of-the-Art Review of Car-Following Models with Particular Considerations of Heavy Vehicles," Transport Reviews, Taylor & Francis Journals, vol. 35(1), pages 82-105, January.
    12. Jiang, Rui & Hu, Mao-Bin & Zhang, H.M. & Gao, Zi-You & Jia, Bin & Wu, Qing-Song, 2015. "On some experimental features of car-following behavior and how to model them," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 338-354.
    13. Peng, Guanghan & Kuang, Hua & Zhao, Hongzhuan & Qing, Li, 2019. "Nonlinear analysis of a new lattice hydrodynamic model with the consideration of honk effect on flux for two-lane highway," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 93-101.
    14. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    15. Zhang, Geng & Zhao, Min & Sun, Di-Hua & Liu, Wei-Ning & Li, Hua-Min, 2016. "Stabilization effect of multiple drivers’ desired velocities in car-following theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 532-540.
    16. Peng, Guanghan & Yang, Shuhong & Xia, Dongxue & Li, Xiaoqin, 2019. "Delayed-feedback control in a car-following model with the combination of V2V communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    17. Robert E. Chandler & Robert Herman & Elliott W. Montroll, 1958. "Traffic Dynamics: Studies in Car Following," Operations Research, INFORMS, vol. 6(2), pages 165-184, April.
    18. 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.
    19. Yu, Shaowei & Zhao, Xiangmo & Xu, Zhigang & Shi, Zhongke, 2016. "An improved car-following model considering the immediately ahead car’s velocity difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 446-455.
    20. Redhu, Poonam & Gupta, Arvind Kumar, 2016. "Effect of forward looking sites on a multi-phase lattice hydrodynamic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 150-160.
    21. Tian, Junfang & Li, Guangyu & Treiber, Martin & Jiang, Rui & Jia, Ning & Ma, Shoufeng, 2016. "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 560-575.
    22. Yang, Da & Qiu, Xiaoping & Yu, Dan & Sun, Ruoxiao & Pu, Yun, 2015. "A cellular automata model for car–truck heterogeneous traffic flow considering the car–truck following combination effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 62-72.
    23. 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.
    24. X. Zhao & Z. Gao, 2005. "A new car-following model: full velocity and acceleration difference model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 47(1), pages 145-150, September.
    25. Kuang, Hua & Xu, Zhi-Peng & Li, Xing-Li & Lo, Siu-Ming, 2017. "An extended car-following model accounting for the average headway effect in intelligent transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 778-787.
    26. Zhang, Jing & Wang, Bo & Li, Shubin & Sun, Tao & Wang, Tao, 2020. "Modeling and application analysis of car-following model with predictive headway variation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    27. Cao, Bao-gui, 2020. "A car-following dynamic model with headway memory and evolution trend," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    Full references (including those not matched with items on IDEAS)

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    5. 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).
    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. Yao, Zhihong & Wang, Yi & Liu, Bo & Zhao, Bin & Jiang, Yangsheng, 2021. "Fuel consumption and transportation emissions evaluation of mixed traffic flow with connected automated vehicles and human-driven vehicles on expressway," Energy, Elsevier, vol. 230(C).

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