IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p15231-d974872.html
   My bibliography  Save this article

Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment

Author

Listed:
  • Junyan Han

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

  • Xiaoyuan Wang

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China
    Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong Province, Qingdao 266100, China)

  • Huili Shi

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

  • Bin Wang

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

  • Gang Wang

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

  • Longfei Chen

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

  • Quanzheng Wang

    (College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266100, China)

Abstract

The type of vehicles in realistic traffic systems are not homogeneous. Impacts of the preceding vehicle’s type on the car-following behavior, fuel consumption and exhaust emissions are still unclear. This paper presents a study on the impacts of two types of preceding vehicles, heavy vehicles and new energy vehicles, on car-following behavior, traffic flow characteristics, fuel consumption and exhaust emissions. Firstly, an extended car-following model was proposed by incorporating the influence of the preceding vehicle’s type. Secondly, impacts of the preceding vehicle’s type on platoon stability were analyzed by applying linear stability theory. Finally, numerical simulations were carried out to analyze impacts of the preceding vehicles’ type on the characteristics of the car-following platoon, traffic flow operation, and vehicle’s fuel consumption and exhaust emissions. The results reveal that, compared with the normal preceding vehicle, there are negative impacts of the heavy and new-energy preceding vehicles on the platoon stability, traffic flow operation, and vehicle’s fuel consumption and exhaust emissions, and these impacts are related to the corresponding sensitivity parameters and the penetration percentages of the two types of preceding vehicle. The research results of this paper can provide a reference for understanding car-following behavior and traffic-flow characteristics affected by the type of preceding vehicles in the V2X environment.

Suggested Citation

  • Junyan Han & Xiaoyuan Wang & Huili Shi & Bin Wang & Gang Wang & Longfei Chen & Quanzheng Wang, 2022. "Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15231-:d:974872
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/15231/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/22/15231/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dewen Kong & Xiucheng Guo & Bo Yang & Dingxin Wu, 2016. "Analyzing the Impact of Trucks on Traffic Flow Based on an Improved Cellular Automaton Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-14, September.
    2. Zhao, Jing & Li, Peng, 2017. "An extended car-following model with consideration of vehicle to vehicle communication of two conflicting streams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 178-187.
    3. 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.
    4. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    5. 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.
    6. Zhao, Jing & Li, Peng, 2016. "An extended car-following model with consideration of speed guidance at intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 1-8.
    7. Peeta, Srinivas & Zhang, Pengcheng & Zhou, Weimin, 2005. "Behavior-based analysis of freeway car-truck interactions and related mitigation strategies," Transportation Research Part B: Methodological, Elsevier, vol. 39(5), pages 417-451, June.
    8. 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.
    9. Sun, Dihua & Kang, Yirong & Yang, Shuhong, 2015. "A novel car following model considering average speed of preceding vehicles group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 103-109.
    10. 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.
    11. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
    12. 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.
    13. Xu, Yueru & Zheng, Yuan & Yang, Ying, 2021. "On the movement simulations of electric vehicles: A behavioral model-based approach," Applied Energy, Elsevier, vol. 283(C).
    14. Yu, Shaowei & Zhao, Xiangmo & Xu, Zhigang & Zhang, Licheng, 2016. "The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 613-628.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    4. Sun, Lu & Jafaripournimchahi, Ammar & Hu, Wusheng, 2020. "A forward-looking anticipative viscous high-order continuum model considering two leading vehicles for traffic flow through wireless V2X communication in autonomous and connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    5. Yang, Qiaoli & Shi, Zhongke, 2018. "Effects of the design of waiting areas on the dynamic behavior of queues at signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 181-195.
    6. Wang, Shutong & Zhu, Wen-Xing, 2022. "Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    7. 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).
    8. Ou, Hui & Tang, Tie-Qiao & Rui, Ying-Xu & Zhou, Jie-Ming, 2018. "Modeling electric bicycle’s abnormal behavior at a signalized intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 218-231.
    9. 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.
    10. Peng, Guanghan & Jia, Teti & Kuang, Hua & Tan, Huili, 2022. "Energy consumption in a new lattice hydrodynamic model based on the delayed effect of collaborative information transmission under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    11. 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.
    12. Chang, Yinyin & He, Zhiting & Cheng, Rongjun, 2019. "An extended lattice hydrodynamic model considering the driver’s sensory memory and delayed-feedback control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 522-532.
    13. Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "A car-following model considering the effect of electronic throttle opening angle over the curved road," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    14. Wang, Pengcheng & Yu, Guizhen & Wu, Xinkai & Qin, Hongmao & Wang, Yunpeng, 2018. "An extended car-following model to describe connected traffic dynamics under cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 351-370.
    15. Chen, Can & Ge, Hongxia & Cheng, Rongjun, 2019. "Self-stabilizing analysis of an extended car-following model with consideration of expected effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    16. Zhang, Geng & Yin, Le & Pan, Dong-Bo & Zhang, Yu & Cui, Bo-Yuan & Jiang, Shan, 2020. "Research on multiple vehicles’ continuous self-delayed velocities on traffic flow with vehicle-to-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    17. 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.
    18. 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).
    19. Chen, Xinyuan & Zhang, Wei & Guo, Xiaomeng & Liu, Zhiyuan & Wang, Shuaian, 2021. "An improved learning-and-optimization train fare design method for addressing commuting congestion at CBD stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15231-:d:974872. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.