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智能网联混合交通流稳定性解析方法综述

蒋阳升 顾秋凡 姚志洪

蒋阳升, 顾秋凡, 姚志洪. 智能网联混合交通流稳定性解析方法综述[J]. 西南交通大学学报, 2022, 57(5): 927-940. doi: 10.3969/j.issn.0258-2724.20210560
引用本文: 蒋阳升, 顾秋凡, 姚志洪. 智能网联混合交通流稳定性解析方法综述[J]. 西南交通大学学报, 2022, 57(5): 927-940. doi: 10.3969/j.issn.0258-2724.20210560
JIANG Yangsheng, GU Qiufan, YAO Zhihong. Review of Stability Analysis Method for Mixed Traffic Flow with Connected Automated Vehicles[J]. Journal of Southwest Jiaotong University, 2022, 57(5): 927-940. doi: 10.3969/j.issn.0258-2724.20210560
Citation: JIANG Yangsheng, GU Qiufan, YAO Zhihong. Review of Stability Analysis Method for Mixed Traffic Flow with Connected Automated Vehicles[J]. Journal of Southwest Jiaotong University, 2022, 57(5): 927-940. doi: 10.3969/j.issn.0258-2724.20210560

智能网联混合交通流稳定性解析方法综述

doi: 10.3969/j.issn.0258-2724.20210560
基金项目: 国家自然科学基金(52002339);四川省科技计划(2022YFG0152,2021YJ0535,2020YFH0026 );广西科技计划(2021AA01007AA);中央高校基本科研业务费专项资金(2682021CX058)
详细信息
    作者简介:

    蒋阳升(1975—),男,教授,博士生导师,研究方向为交通系统建模与优化,E-mail:jiangyangsheng@swjtu.cn

  • 中图分类号: U495

Review of Stability Analysis Method for Mixed Traffic Flow with Connected Automated Vehicles

  • 摘要:

    交通流稳定性分析是研究交通拥堵形成机理、车队队列控制的基础,面向智能网联环境下的混合交通流队列线性稳定性分析已成为近年来的研究热点. 根据受到的扰动大小和范围,介绍了线性稳定性、非线性稳定性、局部稳定性和队列稳定性的相关概念,并指出了交通流队列稳定性的基本判别准则. 基于控制理论,回顾了交通流车队队列线性稳定性条件的经典解析方法,其中,特征方程法评估了交通流内部扰动的增长速度,传递函数法依托于拉普拉斯变换构建了扰动的传递关系. 从经典跟驰模型、考虑时延的跟驰模型和考虑多前车驾驶信息反馈的跟驰模型出发,系统分析并总结了国内外学者对于混合交通流稳定性问题的研究现状,同时回顾了交通流稳定性理论研究在车队队列控制等方面的实验和工程应用. 最后,展望了混合交通流稳定性分析领域的研究前景,指出了在后车跟驰行为、智能网联汽车的交互协同、复杂混合交通流等几个方面是今后需要重点研究的领域.

     

  • 图 1  车辆跟驰运动示意

    Figure 1.  Schematic of car-following motion

    图 2  速度扰动传递函数

    Figure 2.  Transfer function of velocity disturbance

    图 3  经典跟驰模型下的稳定性

    Figure 3.  Stability of basic car-following model

    图 4  多车交互跟驰运动示意

    Figure 4.  Schematic of multivehicle interactive car-following motion

    表  1  智能网联环境下的混合交通流稳定性分析文献总结

    Table  1.   Literature review on stability analysis for mixed traffic flow with connected automated vehicles

    跟驰模型文献车辆类型主要研究方法
    经典跟驰模型[43]ACC + HDV李雅普诺夫稳定性条件
    [44]低带宽 + 中带宽 + 高带宽车辆传递函数法
    [45]ACC + CACC特征方程法
    [46]CACC + ACC + HDVWard混合交通流稳定性条件转化为
    一元二次方程,研究其特性
    [47]CACC + ACC + HDV传递函数法
    [48]CAV + HDV特征方程法
    [49]CAV + HDV特征方程法
    考虑时延的跟驰模型[50]常规车辆 + 半自动车辆传递函数法
    [51]HDV + AV特征方程法
    [34]CAV + HDV特征方程法
    [52]CAV + HDV特征方程法
    [53]CAV + DCAV + HDV特征方程法
    [54]CAV + HDV传递函数法
    [55]CAV + HDV传递函数法
    [56]CACC + ACC + HDV传递函数法
    考虑多前车驾驶
    信息反馈的跟驰模型
    [57]CAV + HDV特征方程法
    [58]CV + HDV特征方程法
    [59]CCC + HDV传递函数法
    [60]CCC + HDV传递函数法
    [61]CAV + HDV特征方程法
    [62]CAV + HDV传递函数法
    [63]CAV + HDV传递函数法
    [64]CAV + HDV传递函数法
    [65]CAV + HDV传递函数法
    [66]CAV + HDV队列稳定性定义
    注:AV (autonomous vehicle)为自动驾驶车辆;CV (connected vehicle)为网联人工驾驶车辆;CCC (connected cruise control)为连通巡航控制车辆.
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    LI Keqiang, DAI Yifan, LI Shengbo, et al. State-of-the-art and technical trends of intelligent and connected vehicles[J]. Journal of Automotive Safety and Energy, 2017, 8(1): 1-14. doi: 10.3969/j.issn.1674-8484.2017.01.001
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出版历程
  • 收稿日期:  2021-07-09
  • 修回日期:  2022-01-22
  • 网络出版日期:  2022-09-01
  • 刊出日期:  2022-03-31

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