IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15295-d1267464.html
   My bibliography  Save this article

Heterogeneous Traffic Flow Signal Control and CAV Trajectory Optimization Based on Pre-Signal Lights and Dedicated CAV Lanes

Author

Listed:
  • Jixiang Wang

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
    Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310052, China)

  • Haiyang Yu

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
    Zhongguancun Laboratory, Beijing 100083, China)

  • Siqi Chen

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
    Hefei Innovation Research Institute, Beihang University, Hefei 230071, China)

  • Zechang Ye

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
    Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310052, China)

  • Yilong Ren

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
    Zhongguancun Laboratory, Beijing 100083, China)

Abstract

This paper proposes a control system to address the efficiency and pollutant emissions of heterogeneous traffic flow composed of human-operated vehicles (HVs) and connected and automated vehicles (CAVs). Based on the comprehensive collection of information on the flow of heterogeneous traffic, the control system uses a two-layer optimization model for signal duration calculation and CAV trajectory planning. The upper model optimizes the phase duration in real time based on the actual total number and type of vehicles entering the control adjustment zone, while the lower model optimizes CAV lane-changing strategies and vehicle acceleration optimization curves based on the phase duration optimized by the upper model. The target function accounts for reducing fuel usage, carbon emission lane-changing costs, and vehicle travel delays. Based on the Webster optimal cycle formula, an improved cuckoo algorithm with strong search performance is created to solve the model. The numerical data confirmed the benefits of the suggested signal control and CAV trajectory optimization method based on pre-signal lights and dedicated CAV lanes for heterogeneous traffic flow. Intersection capacity was significantly enhanced, CAV average fuel consumption, carbon emission and lane-changing frequency were significantly reduced, and traffic flow speed and delay were significantly improved.

Suggested Citation

  • Jixiang Wang & Haiyang Yu & Siqi Chen & Zechang Ye & Yilong Ren, 2023. "Heterogeneous Traffic Flow Signal Control and CAV Trajectory Optimization Based on Pre-Signal Lights and Dedicated CAV Lanes," Sustainability, MDPI, vol. 15(21), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15295-:d:1267464
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15295/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/21/15295/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xuan, Yiguang & Daganzo, Carlos F. & Cassidy, Michael J., 2011. "Increasing the capacity of signalized intersections with separate left turn phases," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 769-781, June.
    2. Yu, Chunhui & Feng, Yiheng & Liu, Henry X. & Ma, Wanjing & Yang, Xiaoguang, 2018. "Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 89-112.
    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. Tang, Liying & Liu, Yugang & Li, JiaLi & Qi, Ruiting & Zheng, Shuai & Chen, Bin & Yang, Hongtai, 2020. "Pedestrian crossing design and analysis for symmetric intersections: Efficiency and safety," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 187-206.
    2. Wang, Tao & Yuan, Zijian & Zhang, Yuanshu & Zhang, Jing & Tian, Junfang, 2023. "A driving guidance strategy with pre-stop line at signalized intersection: Collaborative optimization of capacity and fuel consumption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    3. Zhao, Jing & Knoop, Victor L. & Wang, Meng, 2020. "Two-dimensional vehicular movement modelling at intersections based on optimal control," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 1-22.
    4. Wei Wu & Wanjing Ma & Kejun Long & Heping Zhou & Yi Zhang, 2016. "Designing Sustainable Public Transportation: Integrated Optimization of Bus Speed and Holding Time in a Connected Vehicle Environment," Sustainability, MDPI, vol. 8(11), pages 1-15, November.
    5. Li, Li & Li, Xiaopeng, 2019. "Parsimonious trajectory design of connected automated traffic," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 1-21.
    6. Yu, Chunhui & Ma, Wanjing & Yang, Xiaoguang, 2020. "A time-slot based signal scheme model for fixed-time control at isolated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 176-192.
    7. Xiao Xiao & Yunlong Zhang & Xiubin Bruce Wang & Shu Yang & Tianyi Chen, 2021. "Hierarchical Longitudinal Control for Connected and Automated Vehicles in Mixed Traffic on a Signalized Arterial," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    8. Mohebifard, Rasool & Hajbabaie, Ali, 2019. "Optimal network-level traffic signal control: A benders decomposition-based solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 252-274.
    9. Manivasakan, Hesavar & Kalra, Riddhi & O'Hern, Steve & Fang, Yihai & Xi, Yinfei & Zheng, Nan, 2021. "Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 36-53.
    10. Gao, Yuhong & Qu, Zhaowei & Song, Xianmin & Yun, Zhenyu & Xia, Yingji, 2021. "A novel relationship model between signal timing, queue length and travel speed," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    11. Li, Tongfei & Cao, Yaning & Xu, Min & Sun, Huijun, 2023. "Optimal intersection design and signal setting in a transportation network with mixed HVs and CAVs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    12. Yongtao Zheng & Xuedong Hua & Wei Wang & Jialiang Xiao & Dongya Li, 2020. "Analysis of a Signalized Intersection with Dynamic Use of the Left-Turn Lane for Opposite through Traffic," Sustainability, MDPI, vol. 12(18), pages 1-29, September.
    13. Amirgholy, Mahyar & Gao, H. Oliver, 2023. "Optimal traffic operation for maximum energy efficiency in signal-free urban networks: A macroscopic analytical approach," Applied Energy, Elsevier, vol. 329(C).
    14. Yang Shao & Zhongbin Luo & Huan Wu & Xueyan Han & Binghong Pan & Shangru Liu & Christian G. Claudel, 2020. "Evaluation of Two Improved Schemes at Non-Aligned Intersections Affected by a Work Zone with an Entropy Method," Sustainability, MDPI, vol. 12(14), pages 1-24, July.
    15. Li, Xiang & Sun, Jian-Qiao, 2016. "Effects of turning and through lane sharing on traffic performance at intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 622-640.
    16. Wu, Jiaming & Kulcsár, Balázs & Ahn, Soyoung & Qu, Xiaobo, 2020. "Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 223-239.
    17. Bo Feng & Mingming Zheng & Yan Liu, 2023. "Optimization of Signal Timing for the Contraflow Left-Turn Lane at Signalized Intersections Based on Delay Analysis," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    18. Tan, Jiyuan & Li, Li & Li, Zhiheng & Zhang, Yi, 2013. "Distribution models for start-up lost time and effective departure flow rate," Transportation Research Part A: Policy and Practice, Elsevier, vol. 51(C), pages 1-11.
    19. Lu, Gongyuan & Shen, Zili & Liu, Xiaobo & Nie, Yu (Marco) & Xiong, Zhiqiang, 2022. "Are autonomous vehicles better off without signals at intersections? A comparative computational study," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 26-46.
    20. Chen, Xiangdong & Lin, Xi & Li, Meng & He, Fang & Meng, Qiang, 2023. "A nearly throughput-maximum knotted intersection design and control for connected and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 44-79.

    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:15:y:2023:i:21:p:15295-:d:1267464. 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.