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面向新型混合交通流的快速路合流区通行能力建模

胡笳 安连华 李欣

胡笳, 安连华, 李欣. 面向新型混合交通流的快速路合流区通行能力建模[J]. 交通信息与安全, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016
引用本文: 胡笳, 安连华, 李欣. 面向新型混合交通流的快速路合流区通行能力建模[J]. 交通信息与安全, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016
HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016
Citation: HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016

面向新型混合交通流的快速路合流区通行能力建模

doi: 10.3963/j.jssn.1674-4861.2021.01.016
基金项目: 

国家重点研发项目 2019YFB1600402

国家自然科学基金项目 61803284

国家自然科学基金项目 61903058

上海扬帆计划项目 18YF1424200

中特智能讲席教授基金项目 000000375-2018082

详细信息
    作者简介:

    胡笳(1988—),博士,教授.研究方向:网联自动驾驶技术与交通管控理论. E-mail: hujia@tongji.edu.cn

    通讯作者:

    李欣(1985—),博士,教授.研究方向:城市公共交通运营调度优化理论.E-mail: xtopli@dlmu.edu.cn

  • 中图分类号: U491.2

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

  • 摘要: 面向人类驾驶和具备协同自适应巡航功能的网联自动驾驶组成的新型混合交通流,考虑道路交通特性、道路结构以及匝道汇入前主线交通状态等因素的交互作用机理,基于概率统计理论解析网联自动驾驶渗透率和编队长度间的耦合关系,进一步基于间隙接受理论分析匝道汇入交通对合流区通行能力的折减效应,建立快速路合流区通行能力模型,定量描述不同道路条件下合流区通行能力如何随网联自动驾驶渗透率和编队长度变化。模型中的道路交通特性、道路结构及匝道汇入前部分交通状态参数根据实际道路交通环境标定,提升了模型的通用性与可迁移性。搭建内嵌车辆动力学模块的Vissim仿真平台进行模型评估,结果表明,模型精度在80%以上,且在不同网联自动驾驶渗透率和编队长度条件下皆表现良好。

     

  • 图  1  快速路合流区场景

    Figure  1.  Scenario of freeway merging areas

    图  2  新型混合交通流快速路合流区通行能力基本图

    Figure  2.  Capacity in freeway merging areas under partially CACC traffic

    图  3  新型混合交通流通用仿真框架

    Figure  3.  Genic simulation framework of novel mixed traffic flow

    图  4  快速路合流区路网结构

    Figure  4.  Link structure of freeway merging areas

    图  5  模型评估结果

    Figure  5.  Results of model evaluation

    表  1  模型符号说明

    Table  1.   Model Notations

    符号 含义
    σ 具备CACC编队功能的CAVs渗透率
    σe 匝道汇入后CAVs有效渗透率
    λ 爱尔朗分布形状参数
    ϕ 匝道交通需求,veh/h
    Cmix 新型混合交通流主线道路通行能力,veh/(h·ane)
    C 人类驾驶交通流道路通行能力, veh/(h·ane)
    ${\widetilde {{C_{{\mathop{\rm mix}\nolimits} }}}} $ 混有CACC编队的快速路合流区通行能力,veh/(h·ane)
    D 主线交通需求, veh/h
    ${\varepsilon \left( {\sigma , {N_{\rm{m}}}} \right)} $ 每个CAV的道路临界通行能力平均增益
    ${\varepsilon \left( {{\sigma _e}, {N_{\rm{m}}}} \right)} $ 考虑匝道汇入后每个CAV的道路临界通行能力平均增益, s
    K 爱尔朗分布速率参数
    Nm CACC最大编队长度(即编队长度限制), veh/platoon
    Na CACC实际编队长度, veh/platoon
    $ {{{\bar N}_{\rm{a}}}}$ CACC平均编队长度(即期望编队长度), veh/platoon
    $ {{{\tilde N}_{\rm{a}}}}$ 有效CACC编队长度, veh/platoon
    NG 时间段[0, T] 内匝道汇入主线的车辆数, veh
    N 合流区主线在时间段[0, T] 内通过车辆数, veh
    PG 匝道汇入概率
    SN 编队长度分布标准差, veh/platoon
    ${t_{{\rm{HF}}}^{\min }} $ HVs跟随其他车辆的最小车头时距, s
    $ {t_{{\rm{AF}}}^{\min }}$ CAVs跟随其他车辆的最小车头时距, s
    $ {t_{{\rm{CF}}}^{\min }}$ CACC编队内部的最小车头时距, s
    PAF CAVs为跟随车的概率
    PHF HVs为跟随车的概率
    PCF CAVs处于CACC编队内部的概率
    ${t_{{\rm{mix}}}^{\min }} $ 混合交通流平均最小车头时距, s
    m 主线车道数
    $ {t_{\rm{G}}^{\min }}$ 匝道汇入可接受最小车头时距, s
    $ {\bar t}$ 主线外侧车道平均可穿越车头时距, s
    V 主线车头时距方差, s2
    下载: 导出CSV
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  • 收稿日期:  2020-09-26
  • 刊出日期:  2021-02-28

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