IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v603y2022ics037843712200468x.html
   My bibliography  Save this article

CTM-based traffic signal optimization of mixed traffic flow with connected automated vehicles and human-driven vehicles

Author

Listed:
  • Yao, Zhihong
  • Jin, Yuting
  • Jiang, Haoran
  • Hu, Lu
  • Jiang, Yangsheng

Abstract

This paper proposes a cell transmission model (CTM)-based traffic signal timing model of mixed traffic flow composed of connected automated vehicles (CAVs) and human-driven vehicles (HDVs). Firstly, the CTM of mixed traffic flow is derived from considering the influence of the market penetration rates (MPRs) of CAVs. Secondly, the dynamic evolution is developed to capture the queue accumulation and the congestion dissipation at the entrance of the intersection. Then, the optimization model is proposed based on the constraints of traffic signals and the relationship of flow transmission between adjacent cells. Moreover, the simultaneous perturbation stochastic approximation (SPSA) algorithm is adopted to solve the proposed model. The evolution laws of the density of each entrance with time and space are compared under the fixed and the optimized traffic signals. Finally, the vehicle’s delay is selected as the evaluation index, and the superiority of the optimization model is discussed. The results show that the proposed model can effectively reduce the range and dissipation time of traffic congestion. The average dissipation efficiency of each entrance is increased by 11.11%. Furthermore, the traffic delay gradually decreases with the MPRs of CAVs, and the delay of homogeneous CAVs is 14.81% lower than that of homogeneous HDVs traffic flow. Therefore, the large-scale application of CAVs can alleviate traffic congestion and improve the traffic capacity of the signalized intersection.

Suggested Citation

  • Yao, Zhihong & Jin, Yuting & Jiang, Haoran & Hu, Lu & Jiang, Yangsheng, 2022. "CTM-based traffic signal optimization of mixed traffic flow with connected automated vehicles and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s037843712200468x
    DOI: 10.1016/j.physa.2022.127708
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712200468X
    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.2022.127708?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. Yao, Zhihong & Xu, Taorang & Jiang, Yangsheng & Hu, Rong, 2021. "Linear stability analysis of heterogeneous traffic flow considering degradations of connected automated vehicles and reaction time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    2. Xinghua Hu & Mengyu Huang & Jianpu Guo, 2020. "Feature Analysis on Mixed Traffic Flow of Manually Driven and Autonomous Vehicles Based on Cellular Automata," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-7, November.
    3. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    4. Hong K. Lo, 2001. "A Cell-Based Traffic Control Formulation: Strategies and Benefits of Dynamic Timing Plans," Transportation Science, INFORMS, vol. 35(2), pages 148-164, May.
    5. Treiber, Martin & Kesting, Arne, 2018. "The Intelligent Driver Model with stochasticity – New insights into traffic flow oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 613-623.
    6. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    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. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    2. Kontorinaki, Maria & Spiliopoulou, Anastasia & Roncoli, Claudio & Papageorgiou, Markos, 2017. "First-order traffic flow models incorporating capacity drop: Overview and real-data validation," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 52-75.
    3. 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.
    4. Chi-kwong Wong & Yiu-yin Lee, 2020. "Lane-Based Traffic Signal Simulation and Optimization for Preventing Overflow," Mathematics, MDPI, vol. 8(8), pages 1-28, August.
    5. Chi Xie & Jennifer Duthie, 2015. "An Excess-Demand Dynamic Traffic Assignment Approach for Inferring Origin-Destination Trip Matrices," Networks and Spatial Economics, Springer, vol. 15(4), pages 947-979, December.
    6. Islam, Tarikul & Vu, Hai L. & Hoang, Nam H. & Cricenti, Antonio, 2018. "A linear bus rapid transit with transit signal priority formulation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 163-184.
    7. Douglas Bish & Edward Chamberlayne & Hesham Rakha, 2013. "Optimizing Network Flows with Congestion-Based Flow Reductions," Networks and Spatial Economics, Springer, vol. 13(3), pages 283-306, September.
    8. 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.
    9. Li, Pengfei & Mirchandani, Pitu & Zhou, Xuesong, 2015. "Solving simultaneous route guidance and traffic signal optimization problem using space-phase-time hypernetwork," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 103-130.
    10. Qixiu Cheng & Zhiyuan Liu & Feifei Liu & Ruo Jia, 2017. "Urban dynamic congestion pricing: an overview and emerging research needs," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(0), pages 3-18, August.
    11. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    12. Huanping Li & Jian Wang & Guopeng Bai & Xiaowei Hu, 2021. "Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads," Energies, MDPI, vol. 14(12), pages 1-21, June.
    13. Herrera, Juan C. & Bayen, Alexandre M., 2010. "Incorporation of Lagrangian measurements in freeway traffic state estimation," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 460-481, May.
    14. Jinxiao Duan & Guanwen Zeng & Nimrod Serok & Daqing Li & Efrat Blumenfeld Lieberthal & Hai-Jun Huang & Shlomo Havlin, 2023. "Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    15. Ma, Tao & Zhou, Zhou & Antoniou, Constantinos, 2018. "Dynamic factor model for network traffic state forecast," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 281-317.
    16. Bellei, Giuseppe & Gentile, Guido & Papola, Natale, 2005. "A within-day dynamic traffic assignment model for urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 39(1), pages 1-29, January.
    17. Jin, Wen-Long, 2010. "Continuous kinematic wave models of merging traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1084-1103, September.
    18. Georgia Perakis & Guillaume Roels, 2006. "An Analytical Model for Traffic Delays and the Dynamic User Equilibrium Problem," Operations Research, INFORMS, vol. 54(6), pages 1151-1171, December.
    19. Yang, Lei & Yin, Suwan & Han, Ke & Haddad, Jack & Hu, Minghua, 2017. "Fundamental diagrams of airport surface traffic: Models and applications," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 29-51.
    20. Fatemeh Enayatollahi & Ahmed Osman Idris & M. A. Amiri Atashgah, 2019. "Modelling bus bunching under variable transit demand using cellular automata," Public Transport, Springer, vol. 11(2), pages 269-298, August.

    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:603:y:2022:i:c:s037843712200468x. 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.