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Congestion and energy consumption of heterogeneous traffic flow mixed with intelligent connected vehicles and platoons

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  • Zeng, Junwei
  • Qian, Yongsheng
  • Li, Jiao
  • Zhang, Yongzhi
  • Xu, Dejie

Abstract

In the future, there will inevitably be a mixed driving situation of intelligent connected vehicles and traditional manual driving vehicles. How intelligent connected vehicles affect traditional traffic flow has attracted increasing attention. Based on the different characteristics of these two types of vehicles a two-lane heterogeneous traffic flow cellular automata model of expressway is proposed, and the effects of whether intelligent connected vehicles form platoons and the size of platoons on traffic flow congestion and energy consumption are simulated. The results show that: as the proportion of intelligent connected vehicles and the size of platoons increase, the maximum traffic capacity can be effectively improved. Besides, with the increase of the mixed ratio, the larger the platoon size, the higher the average speed of traffic flow. The platoon can alleviate even eliminate the congestion faster and more thoroughly. However, in the high-density fully intelligent connected vehicles environment, the larger platoon size leads a negative impact on the traffic flow in the form of “moving bottleneck”. When the platoon size is 4, it can maximize the positive effect of the platoon on the traffic flow. Besides, increasing the proportion and shortening the reaction time of intelligent connected vehicles can effectively reduce the average energy consumption. And platoon mode is more conducive to reduce the average energy consumption than the discrete mode, but the platoon size should be controlled within a reasonable range, otherwise too larger platoon size will aggravate the energy consumption in traffic flow.

Suggested Citation

  • Zeng, Junwei & Qian, Yongsheng & Li, Jiao & Zhang, Yongzhi & Xu, Dejie, 2023. "Congestion and energy consumption of heterogeneous traffic flow mixed with intelligent connected vehicles and platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    • Handle: RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122008895
    DOI: 10.1016/j.physa.2022.128331
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    Cited by:

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    9. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2023. "Jamming transition in two-lane lattice model integrating the deception attacks on influx during the lane-changing process under vehicle to everything environment," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    10. Liu, Hang & Zou, Zhiyun & Jiang, Zehao & Chen, Yujiang & Yang, Qingmei & Gao, Jianzhi, 2024. "Method for utilizing the reserved lane capacity: Formation of the mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    11. Yadav, Sunita & Redhu, Poonam, 2024. "Impact of driving prediction on headway and velocity in car-following model under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    12. Yin, Yu-Hang & Lü, Xing & Jiang, Rui & Jia, Bin & Gao, Ziyou, 2024. "Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in ITS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    13. Liu, Keyi & Feng, Tianjun, 2023. "Heterogeneous traffic flow cellular automata model mixed with intelligent controlled vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    14. Chaolun Wang & Wang Xiang & Guiqiu Xu & Xiaomeng Li, 2023. "Effects of Object-Oriented Advance Guidance Signage on Lane-Changing Behaviors at the Mainline Toll Stations of Expressways," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    15. Ren, Wenhao & Zhao, Xiaohua & Li, Haijian & Fu, Qiang, 2024. "Traffic flow impact of mixed heterogeneous platoons on highways: an approach combining driving simulation and microscopic traffic simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    16. Liu, Hongjie & Yuan, Tengfei & Zeng, Xiaoqing & Guo, KaiYi & Wang, Yizeng & Mo, Yanghui & Xu, Hongzhe, 2024. "Eco-driving strategy for connected automated vehicles in mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    17. Chen, Yingda & Li, Keping & Zhang, Lun & Chen, Yili & Xiao, Xue, 2024. "Modeling and analysis of mixed traffic flow capacity and stability considering human-driven vehicle drivers' trust attitude towards intelligent connected vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    18. Wu, Xuelian & Postorino, Maria Nadia & Mantecchini, Luca, 2024. "Impacts of connected autonomous vehicle platoon breakdown on highway," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 650(C).

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