基于组合赋权-改进TOPSIS法的城市慢行三网融合评价方法

冯芝梅; 郭明洋; 贺玉龙; 彭颢

doi:10.3963/j.jssn.1674-4861.2023.04.017

基于组合赋权-改进TOPSIS法的城市慢行三网融合评价方法

doi: 10.3963/j.jssn.1674-4861.2023.04.017

1.
北京工业大学交通工程北京市重点实验室北京 100124
2.
北京市市政专业设计院股份公司北京 100037

基金项目:

重庆市自然科学基金项目 CSTB2022NSCQ-MSX1147

国家重点研发计划项目 2017YFC0803903

详细信息

作者简介:
冯芝梅（1997—），硕士研究生. 研究方向：交通运输工程. E-mail: fzmzjnu@163.com

通讯作者:
贺玉龙（1968—），博士，副教授. 研究方向：交通安全工程. E-mail: ylhe@bjut.edu.cn

中图分类号: U121
计量
- 文章访问数: 418
- HTML全文浏览量: 229
- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2023-02-22
- 网络出版日期: 2023-11-23

A Combined Weighting-improved TOPSIS Method for Evaluating Integration of Urban Greenway-Waterfront Road-municipal Non-motorized Transport Network

1.
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
2.
Beijing Municipal Professional Design Institute Co., Ltd.. Beijing 100037, China

摘要

摘要: 为解决城市绿道、滨水道路、市政慢行道路等城市慢行系统相互独立、衔接不畅的问题，针对现有研究缺乏三网融合水平评价的现状，研究了基于组合赋权-改进TOPSIS模型的三网融合评价方法。传统的TOP-SIS法采用理想解计算贴近度，没有考虑到异常值与实际情况，故运用基于高斯分布的离群点检测法处理极端异常值，建立了1个综合考虑三网融合水平的评价模型。以往路网评价通常是针对单个对象进行研究，而未考虑多个对象融合情况，因此在构建评价指标体系的过程中，根据三网融合因素、慢行道路网络出行特点、居民出行便利性等，并结合实地调查，选取网络连通性、可达性等相关的13个指标。为了避免单一赋权产生的偏重性，本文建立权重组合优化模型使层次分析法和熵权法确定的主客观权重与组合权重的偏离程度最小。本研究以朝阳区慢行系统网络为例进行验证分析，根据位置和功能，将其分成21个绿道段，得到21个评价对象的三网融合情况和综合排名。结果表明：相较于以往的慢行评价方法和经典的评价方法，该改进模型贴近度标准差为0.278，具有更好的区分度，能够更准确地识别影响三网融合程度的主要因素，并根据各个指标权重做出针对性的优化工作。该评价方法可作为提升绿道、滨水道路与市政慢行道路衔接效果的优化指导方法，促进三网融合与慢行道路网络优化。
- 城市交通 /
- 慢行道路网络 /
- 三网融合 /
- 组合赋权-改进TOPSIS法 /
- 地理信息系统
Abstract: In order to solve the problem of mutual independence and poor connection between urban greenways, waterfront roads, and municipal non-motorized transport network. In a view of the lack of existing studies on the evaluation of the level of tri-networks integration, an evaluation method based on the combination of weighting-improved TOPSIS model is investigated. The traditional TOPSIS method uses ideal solutions to calculate closeness without considering outliers and actual conditions. Therefore, an outlier detection method based on Gaussian distribution is used to deal with extreme outliers, and an evaluation model is established to comprehensively assess the level of tri-network integration. Previous methods of evaluating road network are usually conducted on a single object without considering the integration of multiple objects. Therefore, considering factors of the three networks, travel characteristics of non-motorized transport network and residents' travel convenience, an evaluation system and 13 related indicators, including network connectivity, accessibility and other features, are developed from field surveys. In order to avoid the bias generated by a single weighting, this paper establishes an optimization model of weight combination so that the subjective and objective weights determined by Analytic Hierarchy Process (AHP) and entropy weighting method deviate from the combination of weights to the smallest extent. This study takes the non-motorized transport network in Chaoyang District as a case study for model verification. According to location and function, the network is segmented into 21 greenways, and the ranking for three-network integration of the greenways are obtained. Compared with previous evaluation methods, the results show that the standard deviation of closeness from the improved model is 0.278, which yields better distinction for evaluation of network integration. Besides, the proposed model can accurately identify the main factors that affect the integration of the three networks, and make optimization based on the weight of each indicator. Thus, the proposed evaluation method can be used to a reference to optimize and promote the integration of greenways, waterfront roads and municipal non-motorized transport.
- urban traffic /
- slow road network /
- tri-networks integration /
- combined weighting-improved TOPSIS Method /
- GIS

HTML全文

图 1 研究方法流程图

Figure 1. Flow chart of research methods

下载: 全尺寸图片幻灯片

图 2 面域示意图

Figure 2. Area diagram

下载: 全尺寸图片幻灯片

图 3 慢行系统网络连通性指数

Figure 3. Network connectivity index of slow travel system

下载: 全尺寸图片幻灯片

图 4 朝阳区三网可达性

Figure 4. Accessibility of the three networks in Chaoyang District

下载: 全尺寸图片幻灯片

图 5 极端离群值图示

Figure 5. Extreme outlier plot

下载: 全尺寸图片幻灯片

图 6 三网融合典型区域综合评价指标情况

Figure 6. Comprehensive evaluation indicators of typical regions of tri-network integration

下载: 全尺寸图片幻灯片

图 7 两网融合3个典型区域综合评价指标情况

Figure 7. Comprehensive evaluation indicators of three typical regions of the integration of the two networks

下载: 全尺寸图片幻灯片

表 1 三网融合评价指标集

Table 1. Greenway evaluation index set

指标	一级指标	二级指标
U₁	长度	城市绿道和滨水道路长度
U₂	连通性	缓冲区500 m α值
U₃		缓冲区500 m β值
U₄		缓冲区500 m γ值
U₅		缓冲区1 000 m α值
U₆		缓冲区1 000 m β值
U₇		缓冲区1 000 m γ值
U₈	可达性	服务区10 min可达面积
U₉		服务区10 min可达范围公交站
U₁₀		服务区10 min可达范围共享单车
U₁₁		服务区10 min可达范围公交线路
U₁₂		服务区10 min可达范围地铁站
U₁₃		服务区10 min可达范围地铁线路

下载: 导出CSV

表 2 判断矩阵标度值对应表

Table 2. Corresponding table of matrix scale values

标度值	含义
1	表示2个因素相比，具有同样重要性
3	表示2个因素相比，1个因素比另1个因素稍微重要
5	表示2个因素相比，1个因素比另1个因素明显重要
7	表示2个因素相比，1个因素比另1个因素强烈重要
9	表示2个因素相比，1个因素比另1个因素极端重要
2，4，6，8	表示上述2个相邻判断的中值
1~9的倒数	表示相应2因素交换次序比较的重要性

下载: 导出CSV

表 3 可达范围分析

Table 3. Reachability range analysis

时间/min	步行覆盖范围/km²	骑行覆盖范围/km²
0~5	69.96	92.12
5~10	55.57	90.47
10~15	61.26	156.94
15~30	168.36

下载: 导出CSV

表 4 目标层判断矩阵

Table 4. Target layer judgment matrix

指标	U₁	U₂	U₃	U₄	U₅	U₆	U₇	U₈	U₉	U₁₀	U₁₁	U₁₂	U₁₃
U₁	1	$ \frac{1}{5}$	3	$ \frac{1}{5}$	5	$ \frac{1}{5}$	5	1	$ \frac{1}{3}$	$ \frac{1}{3}$	3	$ \frac{1}{3}$	3
U₂	5	1	7	1	9	1	9	5	3	3	7	3	7
U₃	$ \frac{1}{3}$	$ \frac{1}{7}$	1	$ \frac{1}{7}$	3	$ \frac{1}{7}$	3	$ \frac{1}{3}$	$ \frac{1}{5}$	$ \frac{1}{5}$	1	$ \frac{1}{5}$	1
U₄	5	1	7	1	9	1	9	5	3	3	7	3	7
U₅	$ \frac{1}{5}$	$ \frac{1}{9}$	$ \frac{1}{3}$	$ \frac{1}{9}$	1	$ \frac{1}{9}$	1	$ \frac{1}{5}$	$ \frac{1}{7}$	$ \frac{1}{7}$	$ \frac{1}{3}$	$ \frac{1}{7}$	$ \frac{1}{3}$
U₆	5	1	7	1	9	1	9	5	3	3	7	3	7
U₇	$ \frac{1}{5}$	$ \frac{1}{9}$	$ \frac{1}{3}$	$ \frac{1}{9}$	1	$ \frac{1}{9}$	1	$ \frac{1}{5}$	$ \frac{1}{7}$	$ \frac{1}{7}$	$ \frac{1}{3}$	$ \frac{1}{7}$	$ \frac{1}{3}$
U₈	1	$ \frac{1}{5}$	3	$ \frac{1}{5}$	5	$ \frac{1}{5}$	5	1	$ \frac{1}{3}$	$ \frac{1}{3}$	3	$ \frac{1}{3}$	3
U₉	3	$ \frac{1}{3}$	5	$ \frac{1}{3}$	7	$ \frac{1}{3}$	7	3	1	1	5	1	5
U₁₀	3	$ \frac{1}{3}$	5	$ \frac{1}{3}$	7	$ \frac{1}{3}$	7	3	1	1	3	1	5
U₁₁	$ \frac{1}{3}$	$ \frac{1}{7}$	1	$ \frac{1}{7}$	3	$ \frac{1}{7}$	3	$ \frac{1}{3}$	$ \frac{1}{5}$	$ \frac{1}{3}$	1	$ \frac{1}{5}$	1
U₁₂	3	$ \frac{1}{3}$	5	$ \frac{1}{3}$	7	$ \frac{1}{3}$	7	3	1	1	3	1	5
U₁₃	$ \frac{1}{3}$	$ \frac{1}{7}$	1	$ \frac{1}{7}$	3	$ \frac{1}{7}$	3	$ \frac{1}{3}$	$ \frac{1}{5}$	$ \frac{1}{3}$	1	$ \frac{1}{5}$	1

下载: 导出CSV

表 5 各指标权重赋值

Table 5. Assignment of weights to each index

指标	主观权重c_j	客观权重C_j	组合权重w_j
U₁	0.0448	0.102 4	0.071 4
U₂	0.1839	0.026 5	0.111 3
U₃	0.0223	0.016 0	0.019 4
U₄	0.1839	0.022 9	0.109 7
U₅	0.0118	0.017 0	0.014 2
U₆	0.1839	0.032 3	0.114 0
U₇	0.0118	0.015 5	0.013 5
U₈	0.0448	0.128 6	0.083 5
U₉	0.0911	0.167 0	0.126 1
U₁₀	0.0876	0.140 7	0.112 1
U₁₁	0.0232	0.086 9	0.052 6
U₁₂	0.0876	0.171 4	0.126 2
U₁₃	0.0232	0.072 6	0.046 0

下载: 导出CSV

表 6 三网融合相对接近度计算结果

Table 6. Calculation results of the relative proximity of three-network integration

分类	评价对象	熵权-TOPSIS算法		灰色关联分析		组合赋权-改进TOPSIS算法
分类	评价对象	S_i	排序	关联度	排序	S_i	排序
三网	奥森公园段	0.204	10	0.92	15	0.314	9
	北小河段	0.240	8	0.958	8	0.381	7
	朝阳公园段	0.219	9	0.957	10	0.373	8
	红领巾公园段	0.095	14	0.931	14	0.194	16
	亮马河段	0.316	5	0.965	5	0.545	5
	马家湾湿地公园段	0.112	13	0.881	19	0.220	13
	温榆河段	0.241	7	0.85	21	0.308	10
	朝阳绿道示范段	0.962	1	0.999	1	0.995	1
	清河段	0.242	6	0.912	17	0.391	6
两网	常营半马段	0.045	21	0.916	16	0.150	20
	朝来森林公园段	0.088	16	0.956	11	0.195	15
	萧太后河段	0.056	20	0.965	4	0.162	19
	东二环绿道段	0.129	12	0.941	13	0.238	12
	黑桥公园绿道段	0.061	19	0.899	18	0.166	18
	清河营郊野公园段	0.065	18	0.958	17	0.142	21
	日坛公园段	0.095	15	0.96	6	0.203	14
	仰山公园段	0.067	17	0.859	20	0.178	17
	坝河段	0.573	3	0.975	3	0.895	3
	通惠河段	0.601	2	0.983	2	0.964	2
	土城沟段	0.474	4	0.959	7	0.833	4
	仰山河段	0.149	11	0.947	12	0.271	11
	标准差	0.216		0.039		0.278

下载: 导出CSV

参考文献(24)

[1]	住房和城乡建设部. 城市道路工程设计规范(2016年版): CJJ 37—2012[S]. 北京: 中国建筑工业出版社, 2016. Ministry of Housing and Urban-rural Construction. Code for design of urban road engineering(2016): CJJ 37—2012[S]. Beijing: China Architecture & Building Press, 2016. (in Chinese)
[2]	住房和城乡建设部. 城镇绿道工程技术标准: CJJ/ T304-2019[S]. 北京: 中国建筑工业出版社, 2019. Ministry of Housing and Urban-rural Construction. Technical standard for engineering of urban greenway: CJJ/T304-2019[S]. Beijing: China Architecture & Building Press, 2019. (in Chinese)
[3]	刘超, 杨一帆, 杨慧祎, 等. 多维度视角下的城市滨水空间设计策略: 以《北京滨水空间城市设计导则》为例[C]. 2020/ 2021中国城市规划年会暨2021中国城市规划学术季, 中国四川成都: 中国城市规划学会, 2021. LIU C, YANG Y F, YANG H W, et al. Urban waterfront space design strategy from multi-dimensional perspective: a case study of Urban Design Guidelines for Beijing Waterfront[C]. 2020/2021 China Urban Planning Annual Conference and 2021 China Urban Planning Academic Season. Chengdu: Urban Planning Society of China, 2021. (in Chinese)
[4]	聂月明. 考虑慢行交通连通性改善的慢行出行行为分析[D]. 北京: 北京交通大学, 2020. NIE Y M. Study on slow traffic travel behavior considering the improvement of slow traffic connectivity[D]. Beijing: Beijing Jiaotong University, 2020. (in Chinese)
[5]	马瑞. 基于CAE的北京旧城历史街区慢行交通可达性评价研究[D]. 北京: 北京工业大学, 2020. MA R. Research on accessibility evaluation of slow traffic in historical street of Beijing's old city based on CAE[D]. Beijing: Beijing University of Technology, 2020. (in Chinese)
[6]	HU B B, ZHONG Z F, ZHANG Y L, et al. Understanding the influencing factors of bicycle-sharing demand based on residents' trips[J]. Physica A: Statistical Mechanics and Its Applications, 2022, 586: 126472. doi: 10.1016/j.physa.2021.126472
[7]	钱星雨. 公共交通网络可达性测算与改善策略研究[D]. 北京: 北京交通大学, 2021. QIAN X Y. Research on accessibility modelling measurement and improvement strategy of public transport network[D]. Beijing: Beijing Jiaotong University, 2021. (in Chinese)
[8]	朱战强, 黄存忠, 柳林, 等. "绿道-邻里"视角下建成环境对城市绿道使用的影响: 以广州为例[J]. 热带地理, 2019, 39(2): 247-253. https://www.cnki.com.cn/Article/CJFDTOTAL-RDDD201902010.htm ZHU Z Q, HUANG C Z, LIU L, et al. Influence of built environment on urban greenway use from the perspective of greenway-neighborhood relationships: acase study of Guangzhou, China[J]. Tropical Geography, 2019, 39(2): 247-253. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-RDDD201902010.htm
[9]	唐艺家, 裴男才, 施招婉, 等. 广州市绿道网络连通性、可达性及其对城市化的响应[J]. 生态学杂志, 2022, 41(9): 1804-1812. doi: 10.13292/j.1000-4890.202206.004 TANG Y J, PEI N C, SHI Z W, et al. The connectivity and accessibility of Guangzhou greenway network and its response to urbanization[J]. Chinese Journal of Ecology, 2022, 41(9): 1804-1812. (in Chinese) doi: 10.13292/j.1000-4890.202206.004
[10]	ZENG P, XU W X, LIU B B, et al. Walkability assessment of metro catchment area: a machine learning method based on the fusion of subject-objective perspectives[J]. Frontiers in Public Health, 2022, 10(6): 1086277.
[11]	MU T, LAO Y. A study on the walkability of Zijingang east campus of Zhejiang University: based on network distance walk score[J]. Sustainability, 2022, 14(17): 11108. doi: 10.3390/su141711108
[12]	闫欣欣, 袁振洲, 毛思捷, 等. 基于熵权-TOPSIS模型的慢行交通与城市设计协调评价方法[J]. 公路交通科技, 2018, 35(9): 107-114. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201809016.htm YAN X X, YUAN Z Z, MAO S J, et al. Coordination evaluation of non-motorized traffic and urban design based on entropy weight-TOPSIS model[J]. Journal of Highway and Transportation Research and Development, 2018, 35(9): 107-114. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201809016.htm
[13]	施洲, 刘东东, 纪锋, 等. 超大型沉井基础的施工风险评估[J]. 西南交通大学学报, 2021, 56(6): 1241-1249. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106014.htm SHI Z, LIU D D, JI F, et al. Construction risk assessment of super-large open caisson foundation[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1241-1249. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106014.htm
[14]	ZHA S S, GUO Y, HUANG S H, et al. A hybrid MCDM approach based on ANP and TOPSIS for facility layout selection[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2018, 35(6): 1027-1037.
[15]	孔奥, 胥耀方, 段力伟, 等. 考虑社交距离的综合客运枢纽换乘衔接效果评价[J]. 交通信息与安全, 2022, 40(4): 167-176. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS202204018.htm KONG A, XU Y F, DUAN L W, et al. An evaluation of connectivity of transfer in comprehensive passenger transport hubs considering social distance[J]. Journal of Transport Information and Safety, 2022, 40(4): 167-176. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS202204018.htm
[16]	覃文文, 鄢祺阳, 谷金晶, 等. 重载货车驾驶人驾驶风格识别与量化研究[J]. 交通运输系统工程与信息, 2022, 22(4): 137-148. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202204016.htm QIN W W, YAN Q Y, GU J J, et al. Driving style recognition and quantification for heavy-duty truck drivers[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(4): 137-148. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202204016.htm
[17]	翁建军, 刘管江. 基于组合赋权-云模型的水上机场场址评价方法[J]. 交通信息与安全, 2022, 40(2): 126-134. doi: 10.3963/j.jssn.1674-4861.2022.02.015 WENG J J, LIU G J. A site evaluation of water aerodrome based on combined weighting and a cloud model[J]. Journal of Transport Information and Safety, 2022, 40(2): 126-134. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.02.015
[18]	李志军, 向建军, 盛涛, 等. 基于G1-变异系数-KL改进TOPSIS雷达对抗干扰有效性评估[J]. 北京航空航天大学学报, 2021, 47(12): 2571-2578. https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202112018.htm LI Z J, XIANG J J, SHENG T, et al. G1-variation-coefficient-KL based TOPSIS radar jamming effectiveness evaluation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(12): 2571-2578. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202112018.htm
[19]	刘欢, 李昊. 基于改进记分函数和累积前景理论的直觉模糊TOPSIS法[J]. 哈尔滨理工大学学报, 2022, 27(4): 133-141. https://www.cnki.com.cn/Article/CJFDTOTAL-HLGX202204017.htm LIU H, LI H. Intuitionistic fuzzy TOPSIS method based on improved score function and cumulative prospect theory[J]. Journal of Harbin University of Science and Technology, 2022, 27(4): 133-141. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HLGX202204017.htm
[20]	兰格戈, 于洋. 城市建成环境对公共交通为导向的开发效能的影响规律与优化建议[J]. 福州大学学报(自然科学版), 2023, 51(4): 566-573. https://www.cnki.com.cn/Article/CJFDTOTAL-FZDZ202304018.htm LAN G G. YU Y. Exploration of the factors influencing the effectiveness of transit oriented development in the built environment[J]. Journal of Fuzhou University (Natural Science Edition), 2023, 51(4): 566-573. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-FZDZ202304018.htm
[21]	张羽佳. 基于GIS网络分析法的成都市老城区城市公园绿地可达性研究[D]. 雅安: 四川农业大学, 2020. ZHANG Y J. Research on accessibility of urban park green space in old town of Chengdu based on GIS network analysis[D]. Yaan: Sichuan Agricultural University, 2020. (in Chinese)
[22]	ZUO T, WEI H, CHEN N, et al. First-and-last mile solution via bicycling to improving transit accessibility and advancing transportation equity[J]. Cities, 2020, 99: 102614.
[23]	冯焕焕, 邓建华, 葛婷. 引入驾驶风格的熵权法多属性换道决策模型[J]. 交通运输系统工程与信息, 2020, 20(2): 139-144. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202002022.htm FENG H H, DENG J H, GE T. Multi-attributes lane-changing decision model based on entropy weight with driving styles[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 139-144. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202002022.htm
[24]	GONG P, CHEN B, LI X C, et al. Mapping essential urban land use categories in China(EULUC-China): preliminary results for 2018[J]. Science Bulletin, 2020, 65(3): 182-187.