城市轨道交通规划网络与城市规划的综合协调性量化分析

彭其渊; 刘杰

doi:10.19818/j.cnki.1671-1637.2019.03.014

城市轨道交通规划网络与城市规划的综合协调性量化分析

doi: 10.19818/j.cnki.1671-1637.2019.03.014

彭其渊^{1, 2,},
刘杰^{1, 2, ,}

1.
西南交通大学交通运输与物流学院, 四川成都 610031
2.
西南交通大学综合交通运输智能化国家地方联合工程实验室, 四川成都 610031

基金项目:

国家重点研发计划项目 2017YFB1200700

详细信息

作者简介:
彭其渊(1962-), 男, 重庆涪陵人, 西南交通大学教授, 工学博士, 从事轨道交通智能调度研究

通讯作者:
刘杰(1993-), 男, 四川德昌人, 西南交通大学工学博士研究生

中图分类号: U491.12
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出版历程
- 收稿日期: 2019-02-03
- 刊出日期: 2019-06-25

Comprehensive coordination quantitative analysis of urban rail transit planning network and urban planning

PENG Qi-yuan^{1, 2
,},
LIU Jie^{1, 2
, ,}

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
2.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

More Information

Author Bio:
PENG Qi-yuan(1962-), male, professor, PhD, qiyuan-peng@swjtu.edu.cn

Corresponding author: LIU Jie(1993-), male, doctoral student, LIU.Jie@my.swjtu.edu.cn

摘要

摘要: 运用分形理论分析了城市轨道交通规划网络与城市规划在多半径多方向的综合协调性; 基于网络等效长度提出了城市轨道交通规划网络的扇形维数和城市道路规划网络的扇形维数, 基于等效车站提出了城市轨道交通规划车站的扇形维数; 借鉴人口分形维数, 提出了城市交通需求的扇形维数; 运用4个扇形维数, 建立了基于向量相似度和分维一致性的城市轨道交通规划网络与城市规划的综合协调性评估指标; 以南充市2种城市轨道交通规划网络方案为例, 研究了城市轨道交通规划网络与南充市城市规划的综合协调性。研究结果表明: 随着研究半径的增大, 扇形维数的均值逐渐减小, 与城市轨道交通规划网络和城市规划的情况相一致; 城市轨道交通规划网络与城市规划的向量相似度越高, 其在方向上的匹配程度越高; 城市轨道交通规划网络与城市规划的分维一致性越强, 其在研究区域内的协调性越高; 仅从分维一致性不能全面反映城市轨道交通规划网络与城市规划的协调性, 需要结合向量相似度与分维一致性全面分析; 城市轨道交通规划网络与城市规划的协调性随研究半径的变化而改变, 当研究半径分别为3、6、9、12、15 km时, 方案1与南充市城市规划的综合协调性指标分别为0.48、0.45、0.40、0.53、0.43, 方案2与南充市城市规划的协调性指标分别为0.40、0.50、0.48、0.51、0.47;2种方案与城市的协调性指标与实际情况相符合。可见, 本文计算的指标和方法适用于城市轨道交通规划网络与城市规划的综合协调性评价。
- 城市轨道交通 /
- 规划网络 /
- 城市规划 /
- 综合协调性 /
- 分形维数 /
- 向量相似度 /
- 分维一致性
Abstract: The comprehensive coordination between urban rail transit planning network and urban planning in multi-radii and multi-directions was analyzed based on the fractal theory, the sector dimensions of urban rail transit planning network and urban road planning network based on network equivalent length were proposed, and the sector dimension of urban rail transit planning stations based on the equivalent stations was proposed. The sector dimension of urban traffic demand was proposed referring to the fractal dimension of population. The comprehensive coordination evaluation indicator of urban rail transit planning network and urban planning based on the vector similarity and fractal consistency was established by using the four sector dimensions. Taking two schemes of urban rail transit planning network in Nanchong as examples, the comprehensive coordination between urban rail transit planning network and urban planning was analyzed. Analysis result shows that the mean of the sector dimension decreases with the increase of research radius, and it's consistent with the urban rail transit planning network and urban planning. The higher the vector similarity between urban rail transit planning network and urban planning, the higher the matching degree in directions. The stronger the fractal consistency between urban rail transit planning network and urban planning, the better the coordination in the research area. The coordination between urban rail transit planning network and urban planning cannot be fully reflected only from the fractal consistency, it should be analyzed by combining the vector similarity and fractal consistency. The coordination between urban rail transit planning network and urban planning changes with the change of research radius. When the research radius is 3, 6, 9, 12 and 15 km, respectively, the comprehensive coordination indicator between scheme 1 and urban planning in Nanchong is 0.48, 0.45, 0.40, 0.53 and 0.43, respectively, and the comprehensive coordination indicator between scheme 2 and urban planning in Nanchong is 0.40, 0.50, 0.48, 0.51 and 0.47, respectively. The values of coordination indicators between the two schemes and urban planning in Nanchong are consistent with the reality. Therefore, the indicators and method are applicable to the comprehensive coordination evaluation of urban rail transit planning network and urban planning.
- urban rail transit /
- planning network /
- urban planning /
- comprehensive coordination /
- fractal dimension /
- vector similarity /
- fractal consistency

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图 1 研究半径

Figure 1. Research radius

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图 2 南充城市轨道交通规划方案

Figure 2. Urban rail transit network planning schemes in Nanchong

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图 3 规划年南充市交通小区出行密度

Figure 3. Travel densities of traffic district in planning year in Nanchong

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图 4 南充市研究半径变化

Figure 4. Research radius change in Nanchong

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图 5 城市轨道交通规划网络与城市道路规划网络的向量相似度

Figure 5. Vector similarity between urban rail transit planning network and urban road planning network

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图 6 城市轨道交通规划车站与城市交通需求的向量相似度

Figure 6. Vector similarity between urban rail transit planning stations and urban traffic demand

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图 7 城市轨道交通规划网络与城市道路规划网络的分维一致性

Figure 7. Fractal consistency between urban rail transit planning network and urban road planning network

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图 8 城市轨道交通规划车站与城市交通需求的分维一致性

Figure 8. Fractal consistency between urban rail transit planning stations and urban traffic demand

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图 9 城市轨道交通规划网络与城市规划的综合协调性

Figure 9. Comprehensive coordination between urban rail transit network and urban planning

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表 1 南充市中心测算结果

Table 1. Center measurement results in Nanchong

测算方法	交通规划的中心坐标/m	南充市中心坐标/m
节点度中心测算法	(1 356, -3 628)	(1 365, -3 499)
节点紧密度中心测算法	(1 429, -3 494)
节点介数中心计算法	(1 311, -3 375)

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表 2 南充城市轨道交通规划方案对比

Table 2. Comparison of urban rail transit planning schemes in Nanchong

线路	方案1				方案2
线路	长度/km	高峰客流/万人次	车站数	换乘站数	长度/km	高峰客流/万人次	车站数	换乘站数
1	34.2	4.11	26	4	34.2	4.09	26	4
2	28.2	3.55	22	4	17.2	3.49	16	2
3	32.4	3.17	23	3	36.5	3.35	26	4
4	22.0	2.73	14	3	22.7	3.01	18	2

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表 3 不同半径内的z_{i, r}和t_{i, r}

Table 3. z_{i, r}and t_{i, r}in different radii

扇形区域	r=3 km		r=6 km		r=9 km		r=12 km		r=15 km
扇形区域	z_{i, r}	t_{i, r}	z_{i, r}	t_{i, r}	z_{i, r}	t_{i, r}	z_{i, r}	t_{i, r}	z_{i, r}	t_{i, r}
1	1.35	3.55	1.32	3.02	1.37	2.67	1.36	2.40	1.33	1.83
2	1.37	3.57	1.45	3.15	1.42	2.72	1.41	2.45	1.37	1.87
3	1.44	3.64	1.48	3.18	1.46	2.76	1.44	2.48	1.38	1.88
4	1.40	3.60	1.31	3.01	1.34	2.64	1.31	2.35	1.26	1.76
5	1.49	3.69	1.50	3.20	1.46	2.76	1.47	2.52	1.40	1.91
6	1.50	3.70	1.45	3.15	1.34	2.64	1.31	2.35	1.23	1.72
7	1.53	3.73	1.46	3.16	1.43	2.73	1.41	2.45	1.42	1.92
8	1.43	3.63	1.43	3.13	1.45	2.75	1.42	2.46	1.39	1.89
平均值	1.44	3.64	1.42	3.12	1.41	2.71	1.39	2.43	1.35	1.85

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表 4 方案1在不同半径内的u_{i, r}和w_{i, r}

Table 4. u_{i, r}and w_{i, r}of scheme 1 in different radii

扇形区域	r=3 km		r=6 km		r=9 km		r=12 km		r=15 km
扇形区域	u_{i, r}	w_{i, r}	u_{i, r}	w_{i, r}	u_{i, r}	w_{i, r}	u_{i, r}	w_{i, r}	u_{i, r}	w_{i, r}
1	1.19	1.96	1.09	1.79	1.21	1.61	1.20	1.51	1.19	1.43
2	1.26	2.19	1.32	1.86	1.21	1.73	1.20	1.59	1.18	1.41
3	1.34	2.18	1.31	1.94	1.19	1.79	1.22	1.53	1.20	1.43
4	1.17	1.90	1.03	1.77	1.23	1.63	1.23	1.44	1.22	1.46
5	1.26	2.15	1.28	1.86	1.14	1.64	1.13	1.63	1.14	1.37
6	1.15	2.14	1.27	1.75	1.05	1.45	1.13	1.44	1.05	1.29
7	1.25	2.22	1.35	1.85	1.19	1.69	1.22	1.53	1.24	1.48
8	1.28	2.03	1.16	1.88	1.35	1.75	1.30	1.62	1.22	1.46
平均值	1.24	2.10	1.23	1.84	1.20	1.66	1.20	1.54	1.18	1.42

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