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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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    References listed on IDEAS

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    1. Li, Yongfu & Zhao, Hang & Zhang, Li & Zhang, Chao, 2018. "An extended car-following model incorporating the effects of lateral gap and gradient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 177-189.
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    Cited by:

    1. Feng Xu & Weidi Xu & Xiaona Zhang & Yin Wang & Fu Wang, 2023. "Analysis of Traffic Characteristics and Distance Optimization Design between Entrances and Exits of Urban Construction Projects and Adjacent Planar Intersections," Sustainability, MDPI, vol. 15(11), pages 1-24, May.
    2. 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).
    3. 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.

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