IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v635y2024ics0378437124000116.html
   My bibliography  Save this article

Lane management for mixed traffic flow on roadways considering the car-following behaviors of human-driven vehicles to follow connected and automated vehicles

Author

Listed:
  • Zheng, Yuan
  • Yao, Zhihong
  • Xu, Yueru
  • Qu, Xu
  • Ran, Bin

Abstract

The widespread adoption of emerging connected and automated vehicles (CAVs) highlights the need for identifying the roadway capacity of mixed traffic flow with CAVs and human-driven vehicles (HDVs) for future traffic management. Previous studies focus on analyzing the impacts of CAV technologies on the mixed traffic capacity. However, research on how different car-following behaviors of HDVs to follow CAVs affect the mixed traffic capacity is still lacking. This study proposes an analytical formulation of the mixed traffic capacity based on the probability distributions of HDVs and CAVs and three types of behavior willingness (i.e., believer, neutral, and skeptic) of HDV-following-CAV in a mixed traffic environment. The sufficient conditions are derived for mixed traffic capacity to increase or decrease with the behavior willingness and CAV penetration rate. Based on that, an analytical lane management (LM) model is further proposed to determine the optimal number of CAV dedicated lanes (CDLs) and CAV non-dedicated lane (CNL) strategies that maximize the mixed traffic throughput, considering the mixed traffic demand, behavior willingness, and CAV penetration rate. The results from numerical experiments show that the proposed LM strategies can significantly improve mixed traffic throughputs by deploying optimal CDLs and CNL strategies, compared to one without the LM strategy. The mixed traffic throughputs improve and reduce as the trust willingness and skeptic willingness increase and decrease, respectively. Moreover, the increment in CAV penetration rate does not certainly correspond to the high mixed traffic throughputs. The behavior willingness and heterogeneous headways could be jointly considered to guarantee the positive influences of CAV penetration rate on the mixed traffic throughputs when implementing the LM strategy for the mixed traffic flow.

Suggested Citation

  • Zheng, Yuan & Yao, Zhihong & Xu, Yueru & Qu, Xu & Ran, Bin, 2024. "Lane management for mixed traffic flow on roadways considering the car-following behaviors of human-driven vehicles to follow connected and automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    • Handle: RePEc:eee:phsmap:v:635:y:2024:i:c:s0378437124000116
    DOI: 10.1016/j.physa.2024.129503
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124000116
    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.2024.129503?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. 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).
    2. 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.
    3. 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.
    4. 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.
    5. Wu, Yuanyuan & Wang, David Z.W. & Zhu, Feng, 2022. "Influence of CAVs platooning on intersection capacity under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    6. Wang, Hua & Meng, Qiang & Chen, Shukai & Zhang, Xiaoning, 2021. "Competitive and cooperative behaviour analysis of connected and autonomous vehicles across unsignalised intersections: A game-theoretic approach," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 322-346.
    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. 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).
    2. Yao, Zhihong & Li, Le & Liao, Wenbin & Wang, Yi & Wu, Yunxia, 2024. "Optimal lane management policy for connected automated vehicles in mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    3. 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.
    4. 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).
    5. 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).
    6. Qin, Yanyan & Luo, Qinzhong & Xiao, Tengfei & He, Zhengbing, 2024. "Modeling the mixed traffic capacity of minor roads at a priority intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    7. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "A stochastic dynamic network loading model for mixed traffic with autonomous and human-driven vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    8. Qin, Yanyan & Xie, Lulu & Gong, Siyuan & Ding, Fan & Tang, Honghui, 2024. "An optimal lane configuration management scheme for a mixed traffic freeway with connected vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    9. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(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. 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).
    14. 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).
    15. 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.
    16. 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.
    17. Zhang, Fang & Lu, Jian & Hu, Xiaojian, 2022. "Integrated path controlling and subsidy scheme for mobility and environmental management in automated transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    18. 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).
    19. 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).
    20. Zhu, Liling & Tang, Yandong & Yang, Da, 2021. "Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(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:635:y:2024:i:c:s0378437124000116. 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.