IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v629y2023ics0378437123007252.html
   My bibliography  Save this article

Benefit of connectivity on promoting stability and capacity of traffic flow in automation era: An analytical and numerical investigation

Author

Listed:
  • Dong, Jiakuan
  • Luo, Dongyu
  • Gao, Zhijun
  • Wang, Jiangfeng
  • Chen, Lei

Abstract

With the emergence of connected and automated vehicles (CAVs), understanding the impact of such technological advances on traffic flow is vital to prepare for the popularity of CAVs. It has been well documented in the literature that the connectivity feature of CAVs will further benefit the traffic flow by enhancing stability and improving capacity in comparison to automated vehicles (AVs). However, there is little analytical and quantitative evidence to support this statement. In this paper, we attempt to bridge this gap and reveal the potential of connectivity for CAVs in promoting stability and capacity. First, we use a general feedback control structure to model the longitudinal dynamic of AVs. A feedforward link is added to the general structure of AVs to represent the connectivity feature of CAVs. Then, the performance of AVs and CAVs in attenuating disturbance is compared. Moreover, the time headway boundary to maintain string stability is defined and used for capacity analysis. The analytical and numerical results show that (1) the string stable region is enlarged and the potential to attenuate disturbance is promoted with proper tuning of the feedforward gain; (2) the employable time headway is reduced by introducing the communication link. This paper presents a unified framework and a practical procedure for demonstrating the benefit of connectivity on CAVs. The findings in this paper can be served as an analytical foundation and extended with other elaborate models to further understand the benefit of connectivity for CAVs.

Suggested Citation

  • Dong, Jiakuan & Luo, Dongyu & Gao, Zhijun & Wang, Jiangfeng & Chen, Lei, 2023. "Benefit of connectivity on promoting stability and capacity of traffic flow in automation era: An analytical and numerical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    • Handle: RePEc:eee:phsmap:v:629:y:2023:i:c:s0378437123007252
    DOI: 10.1016/j.physa.2023.129170
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123007252
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.129170?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. Montanino, Marcello & Punzo, Vincenzo, 2015. "Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 82-106.
    3. Sun, Jie & Zheng, Zuduo & Sun, Jian, 2018. "Stability analysis methods and their applicability to car-following models in conventional and connected environments," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 212-237.
    4. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
    5. Chen, Danjue & Ahn, Soyoung & Chitturi, Madhav & Noyce, David A., 2017. "Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 196-221.
    6. Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    7. Li, Xiaopeng, 2022. "Trade-off between safety, mobility and stability in automated vehicle following control: An analytical method," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 1-18.
    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. Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    2. Dong, Jiakuan & Gao, Zhijun & Luo, Dongyu & Wang, Jiangfeng & Chen, Lei, 2024. "Impact of beyond-line-of-sight connectivity on the capacity and stability of mixed traffic flow: An analytical and numerical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    3. Montanino, Marcello & Punzo, Vincenzo, 2021. "On string stability of a mixed and heterogeneous traffic flow: A unifying modelling framework," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 133-154.
    4. Yao, Zhihong & Gu, Qiufan & Jiang, Yangsheng & Ran, Bin, 2022. "Fundamental diagram and stability of mixed traffic flow considering platoon size and intensity of connected automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    5. Jiang, Yangsheng & Sun, Siyuan & Zhu, Fangyi & Wu, Yunxia & Yao, Zhihong, 2023. "A mixed capacity analysis and lane management model considering platoon size and intensity of CAVs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    6. Jiang, Yangsheng & Ren, Tingting & Ma, Yuqin & Wu, Yunxia & Yao, Zhihong, 2023. "Traffic safety evaluation of mixed traffic flow considering the maximum platoon size of connected automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    7. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "Integrated deployment of dedicated lane and roadside unit considering uncertain road capacity under the mixed-autonomy traffic environment," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    8. Yang, Yichen & Li, Zuxing & Li, Yabin & Cao, Tianyu & Li, Zhipeng, 2023. "Stability enhancement for traffic flow via self–stabilizing control strategy in the presence of packet loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    9. Dai, Yulu & Yang, Yuwei & Wang, Zhiyuan & Luo, YinJie, 2022. "Exploring the impact of damping on Connected and Autonomous Vehicle platoon safety with CACC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Xin Chang & Xingjian Zhang & Haichao Li & Chang Wang & Zhe Liu, 2022. "A Survey on Mixed Traffic Flow Characteristics in Connected Vehicle Environments," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    11. Liu, Peng & Xu, Shu-Xian & Ong, Ghim Ping & Tian, Qiong & Ma, Shoufeng, 2021. "Effect of autonomous vehicles on travel and urban characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 128-148.
    12. Zhaoming Zhou & Jianbo Yuan & Shengmin Zhou & Qiong Long & Jianrong Cai & Lei Zhang, 2023. "Modeling and Analysis of Driving Behaviour for Heterogeneous Traffic Flow Considering Market Penetration under Capacity Constraints," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    13. Guan, Hao & Wang, Hua & Meng, Qiang & Mak, Chin Long, 2023. "Markov chain-based traffic analysis on platooning effect among mixed semi- and fully-autonomous vehicles in a freeway lane," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 176-202.
    14. Chen, Shuiwang & Hu, Lu & Yao, Zhihong & Zhu, Juanxiu & Zhao, Bin & Jiang, Yangsheng, 2022. "Efficient and environmentally friendly operation of intermittent dedicated lanes for connected autonomous vehicles in mixed traffic environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).
    15. Ma, Ke & Wang, Hao & Ruan, Tiancheng, 2021. "Analysis of road capacity and pollutant emissions: Impacts of Connected and automated vehicle platoons on traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    16. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Impact of dedicated lanes for connected and autonomous vehicle on traffic flow throughput," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 588-597.
    17. Guo, Mengting & Bai, Yang & Li, Xia & Zhou, Wei & Wang, Chunyang & Ma, Xinwei & Gao, Huixin & Xiao, Yuewen, 2023. "Freeway capacity modeling and analysis for traffic mixed with human-driven and connected automated vehicles considering driver behavior characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    18. Umberto Crisalli & Andrea Gemma & Marco Petrelli, 2023. "Investigating the Effects of Automated Vehicles on Large Urban Road Networks: Some Evidence from Rome," Sustainability, MDPI, vol. 15(13), pages 1-10, July.
    19. Weihan Chen & Gang Ren & Qi Cao & Jianhua Song & Yikun Liu & Changyin Dong, 2023. "A Game-Theory-Based Approach to Modeling Lane-Changing Interactions on Highway On-Ramps: Considering the Bounded Rationality of Drivers," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    20. Chen, Shukai & Wang, Hua & Xiao, Ling & Meng, Qiang, 2022. "Random capacity for a single lane with mixed autonomous and human-driven vehicles: Bounds, mean gaps and probability distributions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).

    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:eee:phsmap:v:629:y:2023:i:c:s0378437123007252. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.