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快速路车路协同场景交通流运行效率仿真评价

孙立山 陈颖达 孔德文 张桐 宋咏昌

孙立山, 陈颖达, 孔德文, 张桐, 宋咏昌. 快速路车路协同场景交通流运行效率仿真评价[J]. 交通信息与安全, 2021, 39(1): 155-163. doi: 10.3963/j.jssn.1674-4861.2021.01.0018
引用本文: 孙立山, 陈颖达, 孔德文, 张桐, 宋咏昌. 快速路车路协同场景交通流运行效率仿真评价[J]. 交通信息与安全, 2021, 39(1): 155-163. doi: 10.3963/j.jssn.1674-4861.2021.01.0018
SUN Lishan, CHEN Yingda, KONG Dewen, ZHANG Tong, SONG Yongchang. A Simulation Evaluation of Traffic Flow Efficiency of Urban Expressways under Cooperative Vehicle-infrastructure Scenarios[J]. Journal of Transport Information and Safety, 2021, 39(1): 155-163. doi: 10.3963/j.jssn.1674-4861.2021.01.0018
Citation: SUN Lishan, CHEN Yingda, KONG Dewen, ZHANG Tong, SONG Yongchang. A Simulation Evaluation of Traffic Flow Efficiency of Urban Expressways under Cooperative Vehicle-infrastructure Scenarios[J]. Journal of Transport Information and Safety, 2021, 39(1): 155-163. doi: 10.3963/j.jssn.1674-4861.2021.01.0018

快速路车路协同场景交通流运行效率仿真评价

doi: 10.3963/j.jssn.1674-4861.2021.01.0018
基金项目: 

北京市科技计划课题项目 Z191100002519002

北京市教育委员会科技计划一般项目 KM202110005002

详细信息
    作者简介:

    孙立山(1980—),博士,教授.研究方向:交通运输规划与管理.E-mail: lssun@bjut.edu.cn

    通讯作者:

    孔德文(1989—),博士,讲师.研究方向:交通运输规划与管理.E-mail: kongdw@bjut.edu.cn

  • 中图分类号: U491.2+6

A Simulation Evaluation of Traffic Flow Efficiency of Urban Expressways under Cooperative Vehicle-infrastructure Scenarios

  • 摘要: 为研究车路协同系统在不同车间信息交互水平下对快速路交通流的影响,采集并提取北京市四方桥快速路段早高峰交通流轨迹,同时分析车路协同场景下快速路车辆运行特征,实现对常规驾驶场景和信息交互场景的车辆行驶模型标定。选取期望速度行驶车辆占比、横向车距收缩比、纵向车距收缩比、通行能力拓展比对车辆运行效率进行评价,提出车辆横向偏移距离缩小比用以评价车辆空间占用状况;搭建仿真模型并进行仿真试验,分析不同信息交互水平对交通的影响程度。结果显示,车辆运行效率随信息交互水平的提升而提升,其中通行能力的提升幅度最为显著,车路协同场景下信息交互水平从4级提高到1级,道路通行能力较常规驾驶场景分别拓展了19.42%,28.06%,46.48%,74.62%,仿真时段内其余指标值提升幅度较小。车间信息交互场景下车辆行驶的横向偏移幅度缩小,且在高水平信息交互下缩小比例达到17.33%,表明相同车道宽度下车辆行驶的横向安全性提升。

     

  • 图  1  驾驶行为标定界面

    Figure  1.  Driving-behavior calibration interface

    图  2  北京市四方桥路段

    Figure  2.  Sifang Bridge section in Beijing

    图  3  仿真运行界面

    Figure  3.  Simulation operation interface

    图  4  仿真评价指标变化趋势

    Figure  4.  Variation trend of simulation evaluation indices

    表  1  各类驾驶行为在车路协同场景下的变化对比表

    Table  1.   Comparison of changes in various driving behaviors under vehicle-road collaboration scenarios

    驾驶行为 无信息交互条件下的车辆运行状态 信息交互条件下的车辆运行状态
    跟车行为 驾驶员反应时间较长、车头间距较大、车辆仅可获取可视范围内车辆信息 反应时间缩短,车头间距和车辆行驶速度更稳定(无震荡)、车辆可获取附近一定范围内的车辆信息
    车道变换 驾驶员反应与决策时间较长、等待变道时间较长,容易出现急加急减速行为 驾驶员反应与决策时间较短、等待变道时间较短,车速变化平缓
    下载: 导出CSV

    表  2  仿真模型参数取值

    Table  2.   Parameter values of the simulation model

    模型 参数 1级 2级 3级 4级 现状
    Wiedemann74跟驰模型 平均停车间距/m 1.0 1.5 2.0 2.5 3.0
    附加安全距离/m 1.0 1.5 2.0 2.5 3.0
    安全距离增加部分/m 2.0 2.5 3.0 3.5 3.0
    最大前视距离/m 250 200 150 100 100
    最大后视距离/m 150 120 90 60 80
    观察前方车辆数/pcu 1.0 2.0 3.0 4.0 2.0
    暂时走神持续时间/s 0.3 0.6 0.9 1.2 1.0
    暂时走神概率/% 1.0 2.0 3.0 4.0 4.0
    换道模型 最大减速度/(m/s2) 2.0 3.0 4.0 5.0 5.0
    -1 m/s2的距离/m 100 80 60 40 40
    可接受的减速度/(m/s2) 1.0 1.5 2.0 2.5 3.0
    等待换道消失时间/s 45.0 60 75.0 90 60
    最小车头时距/m 0.5 0.8 1.0 1.25 1.5
    协调刹车的最大减速度/(m/s2) 3.0 2.6 2.2 1.8 1.6
    下载: 导出CSV

    表  3  模型验证结果

    Table  3.   Results of model validation

    标定指标 速度/(m/s) 位置/m
    ME MAE MARE RMSE ME MAE MARE RMSE
    计算值 -0.16 2.14 0.06 2.43 0.17 1.86 0.04 2.17
    下载: 导出CSV

    表  4  仿真输出结果

    Table  4.   Simulation output result

    影响因素 1级 2级 3级 4级 现状
    最大饱和通行能力/[pcu/(h/ln)] 2 284 1 916 1 675 1 562 1 308
    纵向车距/m   3.25   3.55   3.72   3.94   4.32
    横向车距/m   1.83   1.96   2.16   2.31   2.48
    最优速度样本量/pcu 921 903 831 798 541
    车辆平均横向偏移距离/cm   21.94   22.86   24.28   25.34   26.54
    注: 大型车换算系数取2.0[26]
    下载: 导出CSV

    表  5  仿真评价指标计算值

    Table  5.   Calculated values of simulation evaluation indices %

    对比参数 1级 2级 3级 4级 现状
    期望速度行驶车辆占比 30.70 30.10 27.70 26.6 18.0
    横向车距收缩比 26.21 20.97 12.90 6.85
    纵向车距收缩比 24.77 17.82 13.89 8.80
    车辆横向偏移距离缩小比 17.33 13.87 8.53 4.53
    通行能力拓展比 74.62 46.48 28.06 19.42
    下载: 导出CSV
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  • 收稿日期:  2020-12-18
  • 刊出日期:  2021-02-28

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