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断头路打通场景下的路网优化评估

何伟涛 王艳东 宫延鹏 赵剑

何伟涛, 王艳东, 宫延鹏, 赵剑. 断头路打通场景下的路网优化评估[J]. 交通信息与安全, 2021, 39(6): 100-107. doi: 10.3963/j.jssn.1674-4861.2021.06.012
引用本文: 何伟涛, 王艳东, 宫延鹏, 赵剑. 断头路打通场景下的路网优化评估[J]. 交通信息与安全, 2021, 39(6): 100-107. doi: 10.3963/j.jssn.1674-4861.2021.06.012
HE Weitao, WANG Yandong, GONG Yanpeng, ZHAO Jian. An Evaluation Study of Network Optimization through Connecting Dead-end-roads[J]. Journal of Transport Information and Safety, 2021, 39(6): 100-107. doi: 10.3963/j.jssn.1674-4861.2021.06.012
Citation: HE Weitao, WANG Yandong, GONG Yanpeng, ZHAO Jian. An Evaluation Study of Network Optimization through Connecting Dead-end-roads[J]. Journal of Transport Information and Safety, 2021, 39(6): 100-107. doi: 10.3963/j.jssn.1674-4861.2021.06.012

断头路打通场景下的路网优化评估

doi: 10.3963/j.jssn.1674-4861.2021.06.012
基金项目: 

国家重点研发计划项目 2016YFB0501403

详细信息
    作者简介:

    何伟涛(1997—),硕士研究生.研究方向:交通时空大数据分析.E-mail:2019206190019@whu.edu.cn

    通讯作者:

    王艳东(1972—),博士,教授.研究方向:多源图像信息挖掘提取、大数据时空计算. E-mail:ydwang@whu.edu.cn

  • 中图分类号: U491.123

An Evaluation Study of Network Optimization through Connecting Dead-end-roads

  • 摘要: 针对断头路的存在会降低道路利用率、加剧交通拥堵等问题, 构建了断头路打通在路网结构以及交通分配层面上的优化评估方法。在路网结构层面, 采用社区探测对路网进行划分, 获取社区作为受断头路影响较大的路段组合; 在交通分配层面, 将断头路打通带来的影响量化为路段平均速率的变化, 构造路网阻抗函数作为约束条件, 在社区内部进行断头路打通前后2次交通分配; 通过连续平均算法建立求解算法, 选取2次用户均衡状态的路段平均速率变化百分比作为评价指数。以北京市朝阳区路网为算例进行分析, 结果表明: ①900 pcu出行需求约束下, 断头路打通的平均指数均值小于0.6%, 表明在低负荷区域打通断头路不能带来明显的优化; ②在剩余3组较大出行需求约束下, 打通跨社区断头路的评价指数均值(3.097%, 1.833%, 2.633%)都大于打通社区内断头路(2.077%, 1.785%, 2.041%), 在市政工程中应该优先考虑打通跨社区路段。

     

  • 图  1  路网社区划分示意

    Figure  1.  Community division of road network

    图  2  朝阳区道路网

    Figure  2.  Road network of the Chaoyang district

    图  3  待打通路段空间分布

    Figure  3.  Spatial distribution of dead-end roads to be connected

    图  4  社区探测迭代过程

    Figure  4.  Iterative process of community detection

    图  5  社区探测模块度最优结果

    Figure  5.  Optimal results of community detection modularity

    图  6  4种出行需求下的评价指数

    Figure  6.  Evaluation indices of four travel demands

    图  7  跨社区路段与社区内路段评价指数小提琴图

    Figure  7.  Violin chart of evaluation indices for cross-and intra-community road sections

    表  1  道路通行参数设定

    Table  1.   Road traffic parameter setting

    道路等级 限速(/km/h) 通行能力(/单向pcu)
    快速路 80 4 800
    主干路 60 2 800
    次干路 50 1 690
    支路 40 1 640
    其他 30 1 550
    下载: 导出CSV

    表  2  评价指数统计表

    Table  2.   Statistics of evaluation indices

    路段类型 评价指数统计 出行需求/pcu
    900 1 800 2 700 3 600
    跨社区 平均值 -0.445 3.097 1.833 2.633
    标准差 3.317 6.037 3.207 7.844
    社区内 平均值 0.589 2.077 1.785 2.041
    标准差 13.801 11.162 15.230 12.380
    下载: 导出CSV
  • [1] 刘承良, 余瑞林, 曾菊新, 等. 武汉城市圈城乡道路网的空间结构复杂性[J]. 地理科学, 2012, 32(4): 426-433. https://www.cnki.com.cn/Article/CJFDTOTAL-DLKX201204006.htm

    LIU Chengliang, YU Ruilin, ZENG Juxin, et al. Complexity of spatial structure on the urban-rural road network in Wuhan metropolitan area[J]. Geographic Science, 2012, 32(4): 426-433. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLKX201204006.htm
    [2] 李妙君, 孙全欣, 杨静. 瓶颈路段交通改善实证研究[J]. 交通运输系统工程与信息, 2011, 11(增刊1): 201-207. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT2011S1030.htm

    LI Miaojun, SUN Quanxin, YANG Jing. Empirical study for improvingthe traffic conditions at bottleneck road sections[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(S1): 201-207. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT2011S1030.htm
    [3] 曹虹宇. "断头路"成因及对策分析[J]. 绿色建筑, 2016, 8(4): 89-90. doi: 10.3969/j.issn.1004-1672.2016.04.025

    CAO Hongyu. Cause of"Broken Road"and countermeasure[J]. Green Building, 2016, 8(4): 89-90. (in Chinese) doi: 10.3969/j.issn.1004-1672.2016.04.025
    [4] 万幼, 刘耀林. 基于地理加权中心节点距离的网络社区发现算法[J]. 武汉大学学报(信息科学版), 2019, 44(10): 1545-1552. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201910019.htm

    WAN You, LIU Yaolin. Community detection algorithm based on geographical weighted central node distance[J]. Geomatics and Information Science of Wuhan University, 2019, 44(10): 1545-1552. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201910019.htm
    [5] 钱雪娟. 城市路网结构评价方法探讨[J]. 交通科技与经济, 2007(2): 88-90+93. doi: 10.3969/j.issn.1008-5696.2007.02.034

    QIAN Xuejuan. Discussion on evaluating method of city road networks structure[J]. Technology & Economy in Area of Communications, 2007(2): 88-90+93. (in Chinese) doi: 10.3969/j.issn.1008-5696.2007.02.034
    [6] 胡松涛, 张克新, 周业利, 等. 烟台老城区交通微循环改善策略[J]. 交通与运输, 2020, 36(5): 96-100. doi: 10.3969/j.issn.1671-3400.2020.05.023

    HU Songtao, ZHANG Kexin, ZHOU Yeli, et al. Traffic microcirculation improvement strategy in Yantai old town[J]. Traffic and Transportation, 2020, 36(5): 96-100. (in Chinese) doi: 10.3969/j.issn.1671-3400.2020.05.023
    [7] 陈昕, 王媛青, 高令顺. 城市路网中交通盲点开放研究[J]. 辽宁工业大学学报(自然科学版), 2019, 39(2): 91-95+100. https://www.cnki.com.cn/Article/CJFDTOTAL-LNGX201902005.htm

    CHEN Xin, WANG Yuanqing, GAO Lingshun. Research on traffic blind spots opening in urban network[J]. Journal of Liaoning University of Technology(Natural Science Edition), 2019, 39(2): 91-95+100. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LNGX201902005.htm
    [8] MUTHOHAR I, BALIJEPALLI C, PRIYANTO, et al. Analysing vulnerability of road network and guiding evacuees to sheltered areas: Case study of Mt Merapi, Central Java, Indonesia[J]. Case Studies on Transport Policy, 2020, 8(4): 1329-1340. doi: 10.1016/j.cstp.2020.09.004
    [9] ZHENG Yu, LIU Yanchi, YUAN Jing. Urban computing with taxicabs[C]. The 13thInternational Conference on Ubiquitous Computing, Being, China: ACM, 2011.
    [10] KOZASA T, TSUKAI M, FUJIWARA A. A development of dynamic road network planning model considering step-by-st ep construction of links and facility on nodes[C]. 8th International Conference on Traffic and Transportation Studies(ICTTS), Changsha, China: SESC, 2012.
    [11] 杜佳昕, 张丰, 杜震洪, 等. 基于加权流量介数中心性的路网脆弱性分析: 以无锡市为例[J]. 浙江大学学报(理学版), 2020, 47(2): 223-230+243. https://www.cnki.com.cn/Article/CJFDTOTAL-HZDX202002013.htm

    DU Jiaxin, ZHANG Feng, DU Zhenhong, et al. Assessing vulnerability of road networks based on traffic flow betweenness centrality: A case study in Wuxi[J]. Journal of Zhejiang University(Science Edition), 2020, 47(2): 223-230+243. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HZDX202002013.htm
    [12] QIANG Yi, XU Jinwen. Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data[J]. International Journal of Geographical Information Science, 2020, 34(12): 2434-2450. doi: 10.1080/13658816.2019.1694681
    [13] SUGISHITA K, ASAKURA Y. Citation network analysis of vulnerability studies in the fields of transportation and complex networks[J]. Transportation Research Procedia, 2020(47): 369-372. http://www.sciencedirect.com/science/article/pii/S2352146520303082
    [14] CHEN Haiwen, HU Yucong. Finding community structure and evaluating hub road section in urban traffic network[C]. 13th COTA International Conference of Transportation Professionals(CICTP), Shenzhen, China: COTA, 2013.
    [15] 郑黎黎, 杨帆, 孙宝凤, 等. 基于GN算法的城市路网区域划分方法研究[J]. 重庆交通大学学报(自然科学版), 2020, 39(4): 6-10+22. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT202004002.htm

    ZHENG Lili, YANG Fan, SUN Baofen, et al. Urban road network regionalization based on gn algorithm[J]. Jounal of Chongqing Jiaotong University(Nature Science), 2020, 39(4): 6-10+22. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT202004002.htm
    [16] 于晓桦, 晏克非, 牟振华, 等. 基于多级网络的多模式交通配流研究[J]. 交通信息与安全, 2018, 36(1): 103-110+128. doi: 10.3963/j.issn.1674-4861.2018.01.014

    YU Xiaohua, YAN Kefei, MOU Zhenhua, et al. A study of multimodal traffic assignment based on multi-level network[J]. Journal of Transport Information and Safety, 2018, 36(1): 103-110+128. (in Chinese) doi: 10.3963/j.issn.1674-4861.2018.01.014
    [17] TONG Xiaohua, LIANG Dan, JIN Yanmin. A linear road object matching method for conflation based on optimization and logistic regression[J]. International Journal of Geographical Information Science, 2014, 28(4): 824-846. doi: 10.1080/13658816.2013.876501
    [18] 田杭, 郭瑞军. 基于网络负载容量模型的城市路网级联失效研究[J]. 大连交通大学学报, 2019, 40(6): 15-20. https://www.cnki.com.cn/Article/CJFDTOTAL-DLTD201906003.htm

    TIAN Han, GUO Ruijun. Study of urban road network cascading failure based on network load capacity model[J]. Journal of Dalian Jiaotong University, 2019, 40(6): 15-20. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLTD201906003.htm
    [19] SOHOUENOU P Y R, CHRISTIDIS P, CHRISTODOULOU A. Using a random road graph model to understand road networks robustness to link failures[J]. International Journal of Critical Infrastructure Protection, 2020(29): 4-10. http://www.sciencedirect.com/science/article/pii/S1874548220300172
    [20] LENG Junqiang, ZHAI Jing, LI Qianwen, et al. Construction of road network vulnerability evaluation index based on general travel cost[J]. Physica A: Statistical Mechanics and its Applications, 2018(493): 421-429. https://www.sciencedirect.com/science/article/abs/pii/S0378437117310907
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  • 收稿日期:  2021-06-10
  • 网络出版日期:  2022-01-12

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