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

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

1.
武汉大学测绘遥感信息工程国家重点实验室武汉 430079
2.
北京市测绘设计研究院北京 100038

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
计量
- 文章访问数: 947
- HTML全文浏览量: 528
- PDF下载量: 441
- 被引次数: 0
出版历程
- 收稿日期: 2021-06-10
- 网络出版日期: 2022-01-12

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

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
Beijing Institute of Surveying and Mapping, Beijing 100038, China

摘要

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。
- 交通规划 /
- 断头路 /
- 社区探测 /
- 交通分配 /
- 路段平均速率
Abstract: Dead-end-roads(DERs)are widespread in any city, and their presence can reduce the usage of roads and lead to traffic congestions. However, there are limited quantitative methods to assess the impacts of DERs. A new method is proposed to assess their impacts. At the level of road structure, community detection is used to classify the road network, and analyze the community which greatly affected by responded DERs. At the level of traffic assignment, whether a dead-end-road is opening, two simulations are performed in the community mentioned above. On this basis, the percentage change of the average value in roads' speeds is selected as an evaluation index. Then, this method is varified by a case study of the road network in Chaoyang District, Beijing. The results shows that: ①Under the travel demand of 900 pcu, the mean value of indices is less than 0.6%, indicating that opening DERs in the low-load area cannot bring obvious optimization. ② Under three groups of large travel demand, the mean value of indices of cross-community DERs(3.097%, 1.833%, and 2.633%)are higher than which of intra-community DERs(2.077%, 1.785%, and 2.041%). The opening of cross-community road sections should be given priority in municipal projects.
- traffic planning /
- dead-end-road /
- community detection /
- traffic assignment /
- road-sections average speed

HTML全文

图 1 路网社区划分示意

Figure 1. Community division of road network

下载: 全尺寸图片幻灯片

图 2 朝阳区道路网

Figure 2. Road network of the Chaoyang district

下载: 全尺寸图片幻灯片

图 3 待打通路段空间分布

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

下载: 全尺寸图片幻灯片

图 4 社区探测迭代过程

Figure 4. Iterative process of community detection

下载: 全尺寸图片幻灯片

图 5 社区探测模块度最优结果

Figure 5. Optimal results of community detection modularity

下载: 全尺寸图片幻灯片

图 6 4种出行需求下的评价指数

Figure 6. Evaluation indices of four travel demands

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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
路段类型	评价指数统计	900	1 800	2 700	3 600
跨社区	平均值	-0.445	3.097	1.833	2.633
跨社区	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
社区内	标准差	13.801	11.162	15.230	12.380

下载: 导出CSV

参考文献(20)

[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 13^thInternational 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