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The Double Lanes Cell Transmission Model of Mixed Traffic Flow in Urban Intelligent Network

Author

Listed:
  • Wenjing Tian

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Jien Ma

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Lin Qiu

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Xiang Wang

    (College of Rail Transportation, Soochow University, Suzhou 215131, China)

  • Zhenzhi Lin

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Chao Luo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Yao Li

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

  • Youtong Fang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310011, China)

Abstract

The connected and autonomous vehicle (CAV) is promised to ease congestion in the future with the rapid development of related technologies in recent years. To explore the characteristics of mixed-traffic flow and the dynamic transmission mechanism, this paper firstly detailed the car-following model of different vehicle types, establishing the fundamental diagram of the mixed-traffic flow through considering the different penetration rates and fleet size of CAV. Secondly, this paper constructed the lane-changing judgment mechanism based on the random utility theory. Finally, the paper proposed a lane-level dynamic cell transmission process, combined with a lane-changing strategy and cell transmission model. The effectiveness and feasibility of the model are verified using simulation analysis. This model makes a systematic, theoretical analysis from the perspective of the internal operation mechanism of traffic flow, and the lane-level traffic strategy provides a theoretical basis for balancing urban lane distribution and intelligent traffic management and control.

Suggested Citation

  • Wenjing Tian & Jien Ma & Lin Qiu & Xiang Wang & Zhenzhi Lin & Chao Luo & Yao Li & Youtong Fang, 2023. "The Double Lanes Cell Transmission Model of Mixed Traffic Flow in Urban Intelligent Network," Energies, MDPI, vol. 16(7), pages 1-17, March.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3108-:d:1110663
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    References listed on IDEAS

    as
    1. Gong, Siyuan & Du, Lili, 2018. "Cooperative platoon control for a mixed traffic flow including human drive vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 25-61.
    2. Davis, L.C., 2018. "Dynamics of a long platoon of cooperative adaptive cruise control vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 818-834.
    3. Gipps, P. G., 1986. "A model for the structure of lane-changing decisions," Transportation Research Part B: Methodological, Elsevier, vol. 20(5), pages 403-414, October.
    4. Yao, Zhihong & Hu, Rong & Wang, Yi & Jiang, Yangsheng & Ran, Bin & Chen, Yanru, 2019. "Stability analysis and the fundamental diagram for mixed connected automated and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    5. Yao, Zhihong & Gu, Qiufan & Jiang, Yangsheng & Ran, Bin, 2022. "Fundamental diagram and stability of mixed traffic flow considering platoon size and intensity of connected automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    6. Vranken, Tim & Schreckenberg, Michael, 2022. "Modelling multi-lane heterogeneous traffic flow with human-driven, automated, and communicating automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    7. 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.
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