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
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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

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图 1 研究方法流程图

Figure 1. Flow chart of research methods

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图 2 面域示意图

Figure 2. Area diagram

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图 3 慢行系统网络连通性指数

Figure 3. Network connectivity index of slow travel system

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图 4 朝阳区三网可达性

Figure 4. Accessibility of the three networks in Chaoyang District

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图 5 极端离群值图示

Figure 5. Extreme outlier plot

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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

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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

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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

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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

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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

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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

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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

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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

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