IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v615y2023ics0378437123001127.html
   My bibliography  Save this article

A mixed capacity analysis and lane management model considering platoon size and intensity of CAVs

Author

Listed:
  • Jiang, Yangsheng
  • Sun, Siyuan
  • Zhu, Fangyi
  • Wu, Yunxia
  • Yao, Zhihong

Abstract

Traffic flow will be mixed with connected automated vehicles (CAVs) and human-driven vehicles (HDVs) in the future. The randomness of the spatial distribution of different types of vehicles (i.e., CAVs and HDVs) will not be conducive to the stability and safety of traffic flow, leading to the deterioration of traffic capacity. Therefore, reasonable organization and management of the spatial distribution of vehicles in mixed traffic flow are significant for improving the performance of transportation systems. To effectively organize CAVs and realize the management of automated dedicated lanes, this paper proposes a mixed capacity and lane management model considering platoon size and intensity of CAVs. Firstly, the spatial distribution of different headway types is calculated based on a Markov chain model. Secondly, a single-lane capacity model is developed based on the headway distribution. Then, we analyze the sensibility of the model’s parameters, including market penetration rates, platooning intensity, and platoon size of CAVs. Finally, we investigate the relationship between traffic capacity and lane management. Numerical analyses illustrate that the single-lane capacity is improved by increasing the market penetration rate, platoon size, and platooning intensity of CAVs. Moreover, The insight of the lane management model indicates that optimal lane management is associated with the market penetration rate of CAVs. These findings provide a strategy for the operation and management of dedicated lanes of CAVs in the future.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001127
    DOI: 10.1016/j.physa.2023.128557
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123001127
    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.2023.128557?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. Zhou, Fang & Li, Xiaopeng & Ma, Jiaqi, 2017. "Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: Theoretical analysis with generalized time geography," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 394-420.
    2. Han, Xiao PhD & Ma, Rui PhD & Zhang, H. Michael PhD, 2019. "Energy-aware Trajectory Optimization of Connected and Automated Vehicle Platoons through a Signalized Intersection," Institute of Transportation Studies, Working Paper Series qt00d6591g, Institute of Transportation Studies, UC Davis.
    3. Chu, Chih-Peng & Tsai, Jyh-Fa & Hu, Shou-Ren, 2012. "Optimal starting location of an HOV lane for a linear monocentric urban area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 457-466.
    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. Vincent A.C. van den Berg & Erik T. Verhoef, 2015. "Robot Cars and Dynamic Bottleneck Congestion: The Effects on Capacity, Value of Time and Preference Heterogeneity," Tinbergen Institute Discussion Papers 15-062/VIII, Tinbergen Institute, revised 11 Jul 2016.
    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. van den Berg, Vincent A.C. & Verhoef, Erik T., 2016. "Autonomous cars and dynamic bottleneck congestion: The effects on capacity, value of time and preference heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 43-60.
    8. Sala, Marcel & Soriguera, Francesc, 2021. "Capacity of a freeway lane with platoons of autonomous vehicles mixed with regular traffic," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 116-131.
    9. 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.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Di, Yunran & Zhang, Weihua & Ding, Heng & Zheng, Xiaoyan & Ran, Bin, 2024. "Cooperative control of dynamic CAV dedicated lanes and vehicle active lane changing in expressway bottleneck areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    3. 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).
    4. 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).
    5. 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).
    6. 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).

    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. Liu, Zhaocai & Chen, Zhibin & He, Yi & Song, Ziqi, 2021. "Network user equilibrium problems with infrastructure-enabled autonomy," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 207-241.
    2. 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.
    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. Li, Pengbo & Tian, Lijun & Xiao, Feng & Zhu, Hongwei, 2022. "Can day-to-day dynamic model be solved analytically? New insights on portraying equilibrium and accommodating autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 374-395.
    5. 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).
    6. 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).
    7. 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).
    8. 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).
    9. 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.
    10. 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).
    11. Bahrami, Sina & Roorda, Matthew J., 2020. "Optimal traffic management policies for mixed human and automated traffic flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 130-143.
    12. 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).
    13. Gelauff, George & Ossokina, Ioulia & Teulings, Coen, 2019. "Spatial and welfare effects of automated driving: Will cities grow, decline or both?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 277-294.
    14. 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.
    15. Qingyu Luo & Rui Du & Hongfei Jia & Lili Yang, 2022. "Research on the Deployment of Joint Dedicated Lanes for CAVs and Buses," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    16. Zeng, Junwei & Qian, Yongsheng & Wang, Wenhai & Xu, Dejie & Li, Haijun, 2023. "The impact of connected automated vehicles and platoons on the traffic safety and stability in complex heterogeneous traffic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    17. Cong-Jian Liu & Fang-Kai Wang & Zhuang-Zhuang Wang & Tao Wang & Ze-Hao Jiang, 2022. "Autonomous Vehicles for Enhancing Expressway Capacity: A Dynamic Perspective," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    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. 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).
    20. 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).

    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:615:y:2023:i:c:s0378437123001127. 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.