IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v623y2023ics0378437123003916.html
   My bibliography  Save this article

An advanced control strategy for connected autonomous vehicles based on Micro simulation models at multiple intersections

Author

Listed:
  • Wang, Jie
  • Cai, Zhiyu
  • Chen, Yaohui
  • Yang, Peng
  • Chen, Bokui

Abstract

The high controllability and connectivity of connected automated vehicles (CAVs) have created opportunities to enhance the road network’s performance. Considering the case that all vehicles in the road network are CAVs, we build an intersection model in which all CAVs follow a given route through the intersection. We obtain the basic evolution rules of vehicles based on the cellular automata model and design conflict judgment and speed adjustment rules to ensure the passage of CAVs within intersections without conflicts. Further, with the goal of minimizing traffic delays in the road network, we design a coordinated control strategy for multiple intersections by considering the density of downstream vehicles. Finally, we conduct simulation experiments in different traffic scenarios. The results show that as the vehicle arrival rates rise, CAVs’ average delays rise and their average speeds decrease. The growth rate of traffic flow through the intersection slows down when a certain percentage is reached. Meanwhile, the coordinated control strategy for multiple intersections can obtain a minor average delay of vehicles on the road network.

Suggested Citation

  • Wang, Jie & Cai, Zhiyu & Chen, Yaohui & Yang, Peng & Chen, Bokui, 2023. "An advanced control strategy for connected autonomous vehicles based on Micro simulation models at multiple intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
  • Handle: RePEc:eee:phsmap:v:623:y:2023:i:c:s0378437123003916
    DOI: 10.1016/j.physa.2023.128836
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123003916
    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.2023.128836?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. Li, Xiang & Sun, Jian-Qiao, 2019. "Intersection multi-objective optimization on signal setting and lane assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1233-1246.
    2. Wen, Tzai-Hung & Chin, Wei-Chien-Benny & Lai, Pei-Chun, 2017. "Understanding the topological characteristics and flow complexity of urban traffic congestion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 166-177.
    3. Zhao, Han-Tao & Liu, Xin-Ru & Chen, Xiao-Xu & Lu, Jian-Cheng, 2018. "Cellular automata model for traffic flow at intersections in internet of vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 40-51.
    4. Wong, G. C. K. & Wong, S. C., 2002. "A multi-class traffic flow model - an extension of LWR model with heterogeneous drivers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 827-841, November.
    5. Wolf, Dietrich E., 1999. "Cellular automata for traffic simulations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 263(1), pages 438-451.
    6. Yu, Shaowei & Shi, Zhongke, 2015. "The effects of vehicular gap changes with memory on traffic flow in cooperative adaptive cruise control strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 206-223.
    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. Cui, Nan & Chen, Bokui & Zhang, Kai & Zhang, Yi & Liu, Xiaotong & Zhou, Jun, 2019. "Effects of route guidance strategies on traffic emissions in intelligent transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 32-44.
    2. Ren, Weilin & Cheng, Rongjun & Ge, Hongxia, 2021. "Bifurcation analysis for a novel heterogeneous continuum model considering electronic throttle angle changes with memory," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    3. Ding Luo & Oded Cats & Hans Lint, 2020. "Can passenger flow distribution be estimated solely based on network properties in public transport systems?," Transportation, Springer, vol. 47(6), pages 2757-2776, December.
    4. Mohan, Ranju & Ramadurai, Gitakrishnan, 2021. "Multi-class traffic flow model based on three dimensional flow–concentration surface," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    5. Ngoduy, D. & Hoogendoorn, S.P. & Liu, R., 2009. "Continuum modeling of cooperative traffic flow dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(13), pages 2705-2716.
    6. Jin, Wen-Long, 2018. "Unifiable multi-commodity kinematic wave model," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 639-659.
    7. Mei, Yiru & Zhao, Xiaoqun & Qian, Yeqing & Xu, Shangzhi & Li, Zhipeng, 2021. "Effect of self-stabilizing control in lattice hydrodynamic model with on-ramp and off-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    8. Tian, Junfang & Li, Guangyu & Treiber, Martin & Jiang, Rui & Jia, Ning & Ma, Shoufeng, 2016. "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 560-575.
    9. Qingtao, Zhai & Hongxia, Ge & Rongjun, Cheng, 2018. "An extended continuum model considering optimal velocity change with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 774-785.
    10. Qiao, Dian-Liang & Zhang, Peng & Lin, Zhi-Yang & Wong, S.C. & Choi, Keechoo, 2017. "A Runge–Kutta discontinuous Galerkin scheme for hyperbolic conservation laws with discontinuous fluxes," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 309-319.
    11. Wu, Jiaxin & Zhou, Xubing & Peng, Yi & Zhao, Xiaojun, 2022. "Recurrence analysis of urban traffic congestion index on multi-scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    12. Jin, Wen-Long, 2013. "A multi-commodity Lighthill–Whitham–Richards model of lane-changing traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 361-377.
    13. Ngoduy, D., 2008. "Applicable filtering framework for online multiclass freeway network estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 599-616.
    14. Logghe, S. & Immers, L.H., 2008. "Multi-class kinematic wave theory of traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 523-541, July.
    15. Hua, Wei & Yue, Yixiang & Wei, Zhenlin & Chen, Jianhua & Wang, Wenrong, 2020. "A cellular automata traffic flow model with spatial variation in the cell width," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    16. Sun, Qiuxia & Zhang, Yu & Sun, Lu & Li, Qing & Gao, Peng & He, Hao, 2021. "Spatial–temporal differences in operational performance of urban trunk roads based on TPI data: The case of Qingdao," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    17. Ngoduy, D., 2021. "Noise-induced instability of a class of stochastic higher order continuum traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 260-278.
    18. Ronan Keane & H. Oliver Gao, 2021. "Fast Calibration of Car-Following Models to Trajectory Data Using the Adjoint Method," Transportation Science, INFORMS, vol. 55(3), pages 592-615, May.
    19. (Sean) Qian, Zhen & Li, Jia & Li, Xiaopeng & Zhang, Michael & Wang, Haizhong, 2017. "Modeling heterogeneous traffic flow: A pragmatic approach," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 183-204.
    20. Carey, Malachy & Bar-Gera, Hillel & Watling, David & Balijepalli, Chandra, 2014. "Implementing first-in–first-out in the cell transmission model for networks," Transportation Research Part B: Methodological, Elsevier, vol. 65(C), pages 105-118.

    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:623:y:2023:i:c:s0378437123003916. 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.