建成环境对交通小区地铁通勤客流的异质性影响

doi:10.13229/j.cnki.jdxbgxb.20221236

Abstract

Abstract:

This paper using the Geographically Weighted Regression model to fit the relationship between built environment variables and subway passenger flow， and analyzes the influence of significant variables on subway passenger flow. Using the passenger flow data of 63 stations of Xi'an Metro Line 1， 2 and 3 for 5 working days， and ArcGIS to match the passenger flow with the traffic analysis zones. On the basis of the traditional least squares regression model， constructed the GWR model. Considering the impact of GDP per capita， land use mixing degree， parking lot density， intersection density， subway entrance and exit density， etc. on the passenger flow of subway entrances and exits. The following conclusions can be obtained： The GWR model can depict the spatial non-stationarity and influence scale of the interaction between subway commuter passenger flow and built environment variables， and its results are better than the traditional least squares method. Meanwhile， we found that four variables-GDP per capita， land use mixing degree， intersection density， and subway entrance and exit density-have significant effects on subway passenger flow. The attraction of land-use mixing degree to subway commuter traffic is much greater than the density of subway entrances and exits， and more obvious in traffic analysis zones with low degree of land use development and balance.

Key words: urban traffic, built environment, commuting, subway passenger flow, geographically weighted regression model

CLC Number:

U491

Shu-hong MA,Guo-mei LIAO,Yan HUANG,Jun-jie ZHANG. Heterogeneity of built environment on commuter passenger flow of subway in traffic analysis zones[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 1913-1922.

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土地分类	交通小区编号POI类型
土地分类	1	2	3	4	5	6	7	8	9	10	11	…
合计	58	400	1195	861	355	389	344	216	216	928	266	…
商服用地	2	117	499	136	34	114	88	52	134	155	52	…
居住用地	6	20	5	25	4	11	11	8	8	47	13	…
公共设施服务用地	3	72	60	94	68	24	50	31	14	124	23	…
交通设施用地	21	200	302	247	101	101	101	73	9	401	101	…
旅游用地	0	14	2	59	99	5	2	1	1	1	0	…
其他用地	26	7	327	300	49	134	92	50	50	200	77	…

变量类型	变量名称	变量描述	均值	标准差
因变量	高峰客流量	早晚高峰交通小区地铁通勤总客流量/人	6348	5732
社会经济属性	常住人口	研究单元常住人口数/人	1950.00	3632.50
	人口密度	研究单元每平方公里的城市居民数/（人·km^-2）	19.60	19.00
	人均GDP	研究区域人均生产总值/（元·人^-1）	125 000.91	108 484.58
土地利用属性	土地利用混合度	研究单元内平均土地利用混合度	1.18	0.20
	公共服务密度	研究单元内科教文化、医疗等的密度/（个·km^-2）	87.36	94.79
	商服密度	研究单元内餐饮、购物、住宿等的密度/（个·km^-2）	145.19	168.33
	停车场密度	研究单元内停车场密度/（个·km^-2）	52.00	48.81
道路连通性及基础设施属性	交叉口密度	研究单元内交叉口数量与土地面积比/（个·km^-2）	21.06	28.46
	公交车站点密度	研究单元内公交站点密度/（个·km^-2）	8.82	11.09
	地铁出入口密度	地铁站点出入口总数与交通小区面积之比/（个·km^-2）	1.18	0.20

	常住人口	人口密度	人均 GDP	土地利用混合度	公共服务密度	商服密度	停车场密度	交叉口密度	公交车站密度	地铁出入口密度
常住人口	1	-0.334^**	0.019	0.175^*	-0.309^**	-.290^**	-0.347^**	-.268^**	-0.124	-0.247^**
人口密度		1	0.384^**	0.109	0.659^**	0.706^**	0.838^**	0.571^**	0.099	0.317^**
人均GDP			1	-0.250^**	0.388^**	0.498^**	0.371^**	0.349^**	-0.012	-0.009
土地利用混合度				1	0.002	-.189^*	0.024	0.049	0.007	-0.069
公共服务密度					1	0.703^**	0.708^**	0.666^**	0.141	0.431^**
商服密度						1	0.715^**	0.616^**	0.204^*	0.484^**
停车场密度							1	0.654^**	0.258^**	0.291^**
交叉口密度								1	0.308^**	0.313^**
公交车站密度									1	0.111
地铁出入口密度										1

变量	常住人口	人口密度	人均GDP	土地利用混合度	公共服务密度	交叉口密度	公交站点密度	地铁出入口密度
Moran’s I	0.5393	0.4363	0.2554	0.5289	0.6496	0.6246	0.5777	0.3004
E（I）	-0.0084	-0.0084	-0.0084	-0.0084	-0.0084	-0.0084	-0.0084	-0.0084
Z	7.8311	5.5297	3.1333	7.9013	9.1266	8.1205	7.6383	4.5737
P-value	0.0020	0.0020	0.0020	0.0020	0.0020	0.0020	0.0020	0.0020

变量	系数	标准差	t统计量	概率［b］	VIF
截距	-3747.856	3043.245	-1.232	0.220	—
常住人口	0.166	0.134	1.236	0.219	1.322
人口密度	-23.851	32.801	-0.727	0.469	2.164
人均GDP	0.030	0.005	6.002	0.000^**	1.605
土地利用混合度	4795.467	2430.230	1.973	0.050^*	1.278
公共服务密度	2.692	7.149	0.377	0.707	2.560
交叉口密度	-46.449	21.786	-2.132	0.035^*	2.143
公交站点密度	-7.767	60.965	-0.127	0.899	1.136
地铁出入口密度	186.951	44.225	4.227	0.000^**	1.342
Adjusted R²	0.285	—	—	—	—
AICc	2628	—	—	—	—

Heterogeneity of built environment on commuter passenger flow of subway in traffic analysis zones

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