IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt4nd624jd.html
   My bibliography  Save this paper

Eco-friendly Cooperative Traffic Optimization at Signalized Intersections

Author

Listed:
  • Hao, Peng
  • Oswald, David
  • Wu, Guoyuan
  • Barth, Matthew J

Abstract

Surface transportation systems (e.g., arterial roadways with signalized intersections) are inherently inefficient, particularly at higher traffic volumes. In general, both the infrastructure (e.g., traffic signals) and the vehicles operate independently, with little coordination between them. Previous research has shown that implementing strategies that take advantage of infrastructure-tovehicle communication can improve overall mobility and reduce environmental impacts, e.g., the Eco-Approach and Departure (EAD) application that takes advantage of communicating signal phase and timing information to the vehicles. In this paper, the authors build upon this past research to develop a new cooperative traffic operation approach that takes advantage of not only infrastructure-to-vehicle communications, but also vehicle-to-infrastructure communications. This effort integrates a dynamic traffic signalization algorithm together with EAD algorithm to achieve even greater traffic efficiency. The research was carried out in a high-fidelity simulation environment and shows upwards of 15% fuel savings and 85% reductions in waiting time. View the NCST Project Webpage

Suggested Citation

  • Hao, Peng & Oswald, David & Wu, Guoyuan & Barth, Matthew J, 2023. "Eco-friendly Cooperative Traffic Optimization at Signalized Intersections," Institute of Transportation Studies, Working Paper Series qt4nd624jd, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt4nd624jd
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/4nd624jd.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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. 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.
    2. Li, Li & Li, Xiaopeng, 2019. "Parsimonious trajectory design of connected automated traffic," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 1-21.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. 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).
    10. 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).
    11. 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.
    12. 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.
    13. 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.
    14. Li, Li & Jabari, Saif Eddin, 2019. "Position weighted backpressure intersection control for urban networks," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 435-461.
    15. Vinícius Antonio Battagello & Nei Yoshihiro Soma & Rubens Junqueira Magalhães Afonso, 2020. "Computational load reduction of the agent guidance problem using Mixed Integer Programming," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-45, June.
    16. 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).
    17. Mohajerpoor, Reza & Saberi, Meead & Ramezani, Mohsen, 2019. "Analytical derivation of the optimal traffic signal timing: Minimizing delay variability and spillback probability for undersaturated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 45-68.
    18. Xiaoyan Wang & Xi Lin & Meng Li, 2021. "Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles," Papers 2102.07147, arXiv.org.
    19. 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.
    20. Wang, Peirong (Slade) & Li, Pengfei (Taylor) & Chowdhury, Farzana R. & Zhang, Li & Zhou, Xuesong, 2020. "A mixed integer programming formulation and scalable solution algorithms for traffic control coordination across multiple intersections based on vehicle space-time trajectories," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 266-304.

    More about this item

    Keywords

    Engineering; Physical Sciences and Mathematics; Ecodriving; Fuel conservation; Mobile communication systems; Optimization; Traffic signal timing; Traffic simulation;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:cdl:itsdav:qt4nd624jd. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.