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预约出行条件下私家车通勤客流分配方法

白紫秀 焦朋朋 陈越 林坤 云旭

白紫秀, 焦朋朋, 陈越, 林坤, 云旭. 预约出行条件下私家车通勤客流分配方法[J]. 交通信息与安全, 2021, 39(4): 117-124. doi: 10.3963/j.jssn.1674-4861.2021.04.015
引用本文: 白紫秀, 焦朋朋, 陈越, 林坤, 云旭. 预约出行条件下私家车通勤客流分配方法[J]. 交通信息与安全, 2021, 39(4): 117-124. doi: 10.3963/j.jssn.1674-4861.2021.04.015
BAI Zixiu, JIAO Pengpeng, CHEN Yue, LIN Kun, YUN Xu. An Assignment Method of Commuter Flow of Private Cars Under Travel Reservation[J]. Journal of Transport Information and Safety, 2021, 39(4): 117-124. doi: 10.3963/j.jssn.1674-4861.2021.04.015
Citation: BAI Zixiu, JIAO Pengpeng, CHEN Yue, LIN Kun, YUN Xu. An Assignment Method of Commuter Flow of Private Cars Under Travel Reservation[J]. Journal of Transport Information and Safety, 2021, 39(4): 117-124. doi: 10.3963/j.jssn.1674-4861.2021.04.015

预约出行条件下私家车通勤客流分配方法

doi: 10.3963/j.jssn.1674-4861.2021.04.015
基金项目: 

国家自然科学基金项目 51578040

北京市属高校高水平教师队伍建设支持计划项目 CIT & TCD20180324

详细信息
    作者简介:

    白紫秀(1998—), 硕士研究生.研究方向: 交通运输规划与管理、预约出行. E-mail: baizixiu126@126.com

    通讯作者:

    焦朋朋(1984—), 博士, 教授.研究方向: 城市及区域交通规划、智能交通系统.E-mail: jiaopengpeng@bucea.edu.cn

  • 中图分类号: U491

An Assignment Method of Commuter Flow of Private Cars Under Travel Reservation

  • 摘要: 预约能调整城市交通的供需关系, 最大化利用交通资源。针对私家车通勤引发的交通拥堵, 研究了预约出行条件下私家车通勤客流分配方法。将车辆分为受控的预约车辆和不受控的非预约车辆, 道路状态分为可预约状态和不可预约状态, 给出了道路状态判别及车辆行程时间计算方法, 构建了城市通勤私家车的预约出行模型。以Nguyen-Dupuis网络作为算例, 从行程时间和预约数量2个方面评价车辆实施预约出行的效果。结果表明: 预约比例由0%提升至100%时, 路径的行程时间降低20%~30%, 平均行程时间从610 s降低至466 s; 当预约比例为30%时能获得全部预约比例的80%收益; 全部车辆均期望参与预约时, 由于预约需求的不均衡仍有2%的车辆预约失败。得出结论, 当预约出行的比例达到30%~40%时, 即可达到缓解拥堵的预期效果。

     

  • 图  1  一般情况下瓶颈区拥堵原理分析

    Figure  1.  Principle analysis of congestion in the bottleneck area under general conditions

    图  2  预约缓解瓶颈区拥堵原理分析

    Figure  2.  Principle analysis of reservation to relieve congestion in bottleneck areas

    图  3  北京中心城区工作日出行特征

    Figure  3.  Weekday travel characteristics in the central city in Beijing

    图  4  预约出行的流程图

    Figure  4.  Flow of travel reservation

    图  5  Nguyen-Dupuis网络拓扑结构图

    Figure  5.  Nguyen-Dupuis network topology

    图  6  预约车辆分配路径的路网状态

    Figure  6.  Selection of the shortest route from the static road network for assigning reservation vehicles

    图  7  不同比例预约车辆的路径行程时间变化

    Figure  7.  Variation of the travel time of the path for different percentages of reservation vehicles

    图  8  不同比例预约车辆的行程时间及改善效果

    注:获得收益比=获得收益/拥堵损失;潜在收益比=潜在收益/拥堵损失;拥堵损失=平均行程时间-最短行程时间;获得收益=不实施预约出行的平均行程时间-平均行程时间;潜在收益=平均行程时间-全部车辆参与预约的平均行程时间

    Figure  8.  Commuting time and improvement effects of different percentages of reservation vehicles

    图  9  不同预约比例下车辆的预约情况

    Figure  9.  Reservation of vehicles with different reservation ratios

    图  10  不同预约比例下车辆的成功预约比

    Figure  10.  Successful reservation of vehicles with different reservation ratios

    图  11  不同比例下预约车辆的预约名额变化

    注:占比1=(预约名额-成功预约车辆数)/预约名额;占比2=(期望预约车辆数-成功预约车辆数)/期望预约车辆数

    Figure  11.  Changes in the reservation capacity of reserved vehicles under different ratios

    表  1  预约车辆和非预约车辆

    Table  1.   Reservable/non-reservable vehicles

    车辆分类 车辆特点
    预约车辆 车辆数量、出发时间和路线可控
    非预约车辆 车辆数量、出发时间和路线根据历史数据确定,包括不愿意参与预约、预约失败、以及考虑交通随机性的车辆
    下载: 导出CSV

    表  2  可预约道路和不可预约道路

    Table  2.   Reservable/non-reservable roads

    道路分类 车辆特点
    可预约道路 受道路密度限制,车辆数少,车速快, 交通状态好;道路上有预约车辆和非预约车辆
    不可预约道路 不受限制,车辆数多, 车速低,交通状态相较可预约道路差; 道路上仅有非预约车辆
    下载: 导出CSV

    表  3  路段自由流时间和通行能力

    Table  3.   Free travel time and capacity of sections

    路段 自由流时间/s 通行能力/(pcu/h) 路段 自由流时间/s 通行能力/(pcu/h)
    1-5 70 900 8-2 100 900
    1-12 80 900 9-10 100 900
    4-5 90 900 9-13 90 900
    4-9 140 900 10-11 80 900
    5-6 50 900 11-2 90 900
    5-9 90 900 11-3 80 900
    6-7 50 900 12-6 70 900
    6-10 130 900 12-8 150 900
    7-8 50 900 13-3 110 900
    7-11 90 900
    下载: 导出CSV

    表  4  通过节点1-3的路径及行程时间

    Table  4.   Path and travel time of passing nodes 1-3

    路径 自由流速度行程时间/s 期望速度行程时间/s
    1-5-9-13-3 360 453.65
    1-5-9-10-11-3 420 529.25
    1-5-6-10-11-3 410 516.65
    1-5-6-7-11-3 340 428.44
    1-12-6-10-11-3 440 554.46
    1-12-6-7-11-3 370 466.25
    下载: 导出CSV
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  • 收稿日期:  2021-03-31

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