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A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons

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  • Jiang, Yangsheng
  • Wang, Sichen
  • Yao, Zhihong
  • Zhao, Bin
  • Wang, Yi

Abstract

With the development of automated driving technology and communication technology, the emergence of connected automated vehicles (CAVs) will significantly improve traffic efficiency and safety. To study the influence of connected automated vehicles (CAVs) on mixed traffic flow, this study proposes a cellular automata (CA) model of mixed traffic flow considering the driving behavior of the platoon of CAVs. Firstly, three car-following modes, Human-driven vehicle (HDV), Adaptive Cruise Control (ACC), and Cooperative Adaptive Cruise Control (CACC), in mixed traffic flow are analyzed. Secondly, on the bias of the safety distance model and platoon behavior analysis, the acceleration, deceleration, and randomization rules of the cellular automata model of mixed traffic flow are developed. The time step is introduced into the model in the rule design, and the reaction time of the vehicle is considered in the randomization rule. Finally, a numerical simulation is conducted to analyze the fundamental diagram of mixed traffic flow, traffic congestion, and speed volatility under different penetration rates of CAVs. The result shows that (1) the road capacity under the pure CAV environment has increased by 3.24 times compared with the pure HDVs; (2) the maximum congestion reduction percentage can reach 63.36%; and (3) when the penetration rate reaches 80%, the velocity fluctuation decreases significantly. Sensitivity analysis shows that when the penetration rate of CAVs is 100%, the maximum platoon size increase can improve the road capacity. Furthermore, the maximum platoon size has an optimal value in a specific density range.

Suggested Citation

  • Jiang, Yangsheng & Wang, Sichen & Yao, Zhihong & Zhao, Bin & Wang, Yi, 2021. "A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    • Handle: RePEc:eee:phsmap:v:582:y:2021:i:c:s0378437121005355
    DOI: 10.1016/j.physa.2021.126262
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    3. Tamakloe, Reuben & Park, Dongjoo, 2023. "Discovering latent topics and trends in autonomous vehicle-related research: A structural topic modelling approach," Transport Policy, Elsevier, vol. 139(C), pages 1-20.
    4. Auwal Alhassan Musa & Salim Idris Malami & Fayez Alanazi & Wassef Ounaies & Mohammed Alshammari & Sadi Ibrahim Haruna, 2023. "Sustainable Traffic Management for Smart Cities Using Internet-of-Things-Oriented Intelligent Transportation Systems (ITS): Challenges and Recommendations," Sustainability, MDPI, vol. 15(13), pages 1-15, June.
    5. Jiang, Yangsheng & Ren, Tingting & Ma, Yuqin & Wu, Yunxia & Yao, Zhihong, 2023. "Traffic safety evaluation of mixed traffic flow considering the maximum platoon size of connected automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    6. Li, Linheng & Wang, Can & Zhang, Ying & Qu, Xu & Li, Rui & Chen, Zhijun & Ran, Bin, 2022. "Microscopic state evolution model of mixed traffic flow based on potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    7. Zhang, Jiahe & Qian, Yongsheng & Zeng, Junwei & Wei, Xuting & Li, Haijun, 2023. "Hybrid characteristics of heterogeneous traffic flow mixed with electric vehicles considering the amplitude of acceleration and deceleration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    8. Li, Haijian & Zhang, Junjie & Sun, Xiaoliang & Niu, Jun & Zhao, Xiaohua, 2022. "A survey of vehicle group behaviors simulation under a connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. Li, Xia & Xiao, Yuewen & Zhao, Xiaodong & Ma, Xinwei & Wang, Xintong, 2023. "Modeling mixed traffic flows of human-driving vehicles and connected and autonomous vehicles considering human drivers’ cognitive characteristics and driving behavior interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    10. Wu, Yuanyuan & Wang, David Z.W. & Zhu, Feng, 2022. "Influence of CAVs platooning on intersection capacity under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    11. 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).
    12. Zhang, Yan-Tao & Hu, Mao-Bin & Chen, Yu-Zhang & Shi, Cong-Ling, 2023. "Cooperative platoon forming strategy for connected autonomous vehicles in mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    13. Raffaele Mauro & Andrea Pompigna, 2022. "A Statistically Based Model for the Characterization of Vehicle Interactions and Vehicle Platoons Formation on Two-Lane Roads," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    14. Guangyang Hou, 2023. "Evaluating Efficiency and Safety of Mixed Traffic with Connected and Autonomous Vehicles in Adverse Weather," Sustainability, MDPI, vol. 15(4), pages 1-19, February.

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