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车路协同环境城市快速路分流区通行能力提升策略

李锐 冉斌 曲栩

李锐, 冉斌, 曲栩. 车路协同环境城市快速路分流区通行能力提升策略[J]. 交通运输工程学报, 2022, 22(3): 126-138. doi: 10.19818/j.cnki.1671-1637.2022.03.010
引用本文: 李锐, 冉斌, 曲栩. 车路协同环境城市快速路分流区通行能力提升策略[J]. 交通运输工程学报, 2022, 22(3): 126-138. doi: 10.19818/j.cnki.1671-1637.2022.03.010
LI Rui, RAN Bin, QU Xu. Traffic capacity enhancement strategy for urban expressway diversion area under vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 126-138. doi: 10.19818/j.cnki.1671-1637.2022.03.010
Citation: LI Rui, RAN Bin, QU Xu. Traffic capacity enhancement strategy for urban expressway diversion area under vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 126-138. doi: 10.19818/j.cnki.1671-1637.2022.03.010

车路协同环境城市快速路分流区通行能力提升策略

doi: 10.19818/j.cnki.1671-1637.2022.03.010
基金项目: 

国家重点研发计划 2018YFB1600600

详细信息
    作者简介:

    李锐(1984-),男,河南洛阳人,河海大学教授,工学博士,从事智能交通系统研究

    通讯作者:

    曲栩(1982-),男,山东青岛人,东南大学副教授,工学博士

  • 中图分类号: U491.112

Traffic capacity enhancement strategy for urban expressway diversion area under vehicle-infrastructure cooperative environment

Funds: 

National Key Research and Development Program of China 2018YFB1600600

More Information
Article Text (Baidu Translation)
  • 摘要: 根据车路协同环境城市快速路分流区不同车型的自动、人工驾驶混合车流特征,引入动态加速度、可变换道概率改进元胞自动机模型车流运行规则;设计了考虑主路自动驾驶渗透率、大型车混入率、驶出自动驾驶渗透率、驶出车流率、出口匝道车道数、换道决策点距离等因素耦合作用的分流区换道仿真试验;对比分析了多因素耦合作用下驶出车辆自由换道率、平均换道距离等指标影响程度,研究了城市快速路分流区道路通行能力变化规律;提出了基于可变换道决策点距离的分流区道路混合车流通行能力提升策略。研究结果表明:分流区驶出车辆自由换道率越高,道路通行能力越大;主路车流自动驾驶渗透率对通行能力的影响最为显著,自动驾驶环境可达到人工驾驶环境道路通行能力的2倍;出口匝道车道数对通行能力的影响不显著,2条出口匝道比1条出口匝道的通行能力提升约3%;换道决策点距离对通行能力的影响较为显著,车辆换道决策点距离从100 m增加到150 m时,分流区道路通行能力可提高9.6%~10.6%。可见,可借助移动式交通标志提前引导车辆换道决策,显著提高分流区道路通行能力。

     

  • 图  1  仿真场景4的流量-自由换道率散点分布

    Figure  1.  Scatter distribution of flow-Rf for simulation scenario 4

    图  2  仿真场景4的流量-自由换道率区段分布

    Figure  2.  Section distribution of flow-Rf for simulation scenario 4

    图  3  仿真场景4的流量-自由换道率拟合曲线

    Figure  3.  Fitting curves of flow-Rf for simulation scenario 4

    图  4  仿真场景4的流量-换道距离拟合曲线

    Figure  4.  Fitting curves of flow-d for simulation scenario 4

    图  5  不同Ro水平下人工、自动、混行车辆换道特征拟合曲线

    Figure  5.  Fitting curves of lane-changing characteristics for AVs, HVs and MVs under different Ro levels

    图  6  不同Ra水平下混行车辆流量-自由换道率拟合曲线

    Figure  6.  Fitting curves of flow-Rf for MVs under different Ra levels

    图  7  不同Ra水平下混行车辆流量-换道距离拟合曲线

    Figure  7.  Fitting curves of flow-d for MVs under different Ra levels

    图  8  不同Rl水平下混行车辆流量-自由换道率拟合曲线

    Figure  8.  Fitting curves of flow-Rf for MVs under different Rl levels

    图  9  不同Rl水平下混行车辆流量-换道距离拟合曲线

    Figure  9.  Fitting curves of flow-d for MVs under different Rl levels

    图  10  不同Rt水平下混行车辆流量-自由换道率拟合曲线

    Figure  10.  Fitting curves of flow-Rf for MVs under different Rt levels

    图  11  不同Rt水平下混行车辆流量-换道距离拟合曲线

    Figure  11.  Fitting curves of flow-d for MVs under different Rt levels

    图  12  不同nl水平下混行车辆流量-自由换道率拟合曲线

    Figure  12.  Fitting curves of flow-Rf for MVs under different nl levels

    图  13  不同nl水平下混行车辆流量-换道距离拟合曲线

    Figure  13.  Fitting curves of flow-d for MVs under different nl levels

    图  14  不同L水平下混行车辆流量-自由换道率拟合曲线

    Figure  14.  Fitting curves of flow-Rf for MVs under different L levels

    图  15  不同L水平下混行车辆流量-换道距离拟合曲线

    Figure  15.  Fitting curves of flow-d for MVs under different L levels

    图  16  不同RtnlL混行车辆流量-自由换道率拟合曲线

    Figure  16.  Fitting curves of flow-Rf for MVs under different Rt, nl and L

    图  17  不同RtnlL混行车辆流量-换道距离拟合曲线

    Figure  17.  Fitting curves of flow-d for MVs under different Rt, nl and L

    图  18  不同因素(RoRaRlRtnlL)影响下分流区仿真拟合

    Figure  18.  Diversion areas simulation fitting under influences of different factors (Ro, Ra, Rl, Rt, nl and L)

    图  19  不同限速(60、70、80 km·h-1)影响下分流区仿真拟合

    Figure  19.  Diversion areas simulation fitting under influences of different speed limits (60, 70, 80 km·h-1)

    图  20  分流区效率提升策略流程

    Figure  20.  Flow of diversion areas efficiency enhancement strategy

    1.  Scatter distribution of flow–Rf in scenario 4

    2.  Section distribution of flow–Rf in scenario 4

    3.  Fitted curves of flow–Rf in scenario 4

    4.  Fitted curves of flow–d in scenario 4

    5.  Fitted curves of lane-changing characteristics for AVs, HVs, and MVs under different Ro

    6.  Fitted curves of flow–Rf for MVs under different Ra

    7.  Fitted curves of flow–d for MVs under different Ra

    8.  Fitted curves of flow–Rf for MVs under different Rl

    9.  Fitted curves of flow–d for MVs under different Rl

    10.  Fitted curves of flow–Rf for MVs under different Rt

    11.  Fitted curves of flow–d for MVs under different Rt

    12.  Fitted curves of flow–Rf for MVs under different nl

    13.  Fitted curves of flow–d for MVs under different nl

    14.  Fitted curves of flow–Rf for MVs under different L

    15.  Fitted curves of flow–d for MVs under different L

    16.  Fitted curves of flow–Rf for MVs under different Rt, nl, and L

    17.  Fitted curves of flow–d for MVs under different Rt, nl, and L

    18.  Fitted curves of diversion areas under different factors (Ro, Ra, Rl, Rt, nl, and L)

    19.  Fitted curves of diversion areas under different speed limits (60, 70, 80 km·h−1)

    20.  Efficiency improvement strategy of diversion areas

    表  1  29种仿真场景的参数

    Table  1.   Parameters of 29 simulation scenarios

    仿真场景 Rt/% Ra/% Ro/% Rl/% nl L/m
    1 20 40 0 4 1 100
    2 20 40 20 4 1 100
    3 20 40 40 4 1 100
    4 20 40 60 4 1 100
    5 20 40 80 4 1 100
    6 20 40 100 4 1 100
    7 20 0 0 4 1 100
    8 20 20 60 4 1 100
    9 20 60 60 4 1 100
    10 20 80 60 4 1 100
    11 20 100 60 4 1 100
    12 20 40 60 2 1 100
    13 20 40 60 6 1 100
    14 20 40 60 8 1 100
    15 20 40 60 10 1 100
    16 10 40 60 4 1 100
    17 15 40 60 4 1 100
    18 25 40 60 4 1 100
    19 30 40 60 4 1 100
    20 20 40 60 2 2 100
    21 20 40 60 4 2 100
    22 20 40 60 8 2 100
    23 15 40 60 4 1 150
    24 20 40 60 4 1 150
    25 25 40 60 4 1 150
    26 20 40 60 8 1 150
    27 20 80 60 4 1 150
    28 20 80 60 8 1 100
    29 20 80 60 8 1 150
    下载: 导出CSV

    1.   Parameters of 29 simulation scenarios

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  • 收稿日期:  2022-01-08
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