网约车出行需求影响因素多尺度空间异质性分析

doi:10.13229/j.cnki.jdxbgxb.20230789

Abstract

Abstract:

In order to explore the influential mechanism of multi-scale ride-hailing travel demand， the travel demand of ride-hailing are analyzed based on the multi-source data. Constructs a multi-scale geographically weighted regression （MGWR） model with short and long distance ride-hailing travel demand as the dependent variable. The effects of built environmental attributes such as road network， land use， population density and public transportation on the demand for ride-hailing and their spatial heterogeneity were revealed. The model results show that the fit of the multi-scale geographical weighted regression model is better than the traditional geographical weighted regression （GWR） model and the ordinary least square （OLS） model， and the influential factors for ride-hailing travel demand have significant spatial heterogeneity. The primary roads density is positively correlated with the short-distance ride-hailing in the city center， and negatively correlated with long-distance ride-hailing in the city periphery. Population density is positively correlated with long-distance ride-hailing in the suburbs， and negatively correlated with the demand for short-distance ride-hailing in the central urban area. Short-distance ride-hailing competes with public transport in the urban centers， while long-distance ride-hailing complements the lack of public transport services around the city. The findings can not only dynamically optimize vehicle configuration and scheduling， but also promote the sustainable development of ride-hailing and shared mobility.

Key words: engineering of communications and transportation system, ride-hailing shared mobility, spatial heterogeneity, built environment, multi-scale geographically weighted regression

CLC Number:

U491

Yi-yong PAN,Jia-cong XU,Yi-wen YOU,Yong-jun QUAN. Multi-scale spatial heterogeneity analysis of influencing factors of ride-hailing travel demand[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(5): 1567-1575.

Figures/Tables 6

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Table 1

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References 25

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变量	描述	平均值	标准差
因变量
LDT	工作日长距离网约车订单量	1 280.19	3 796.45
SDT	工作日短距离网约车订单量	1 280.37	6 034.85
道路网指标
主干路X₁	主干路密度/（km·km^-2）	3.63	3.33
次干路X₂	次干路密度/（km·km^-2）	6.44	13.19
支路X₃	支路密度/（km·km^-2）	4.06	3.44
土地利用指标
人口分布X₄	人口密度/（人·km^-2）	3 928.26	6 048.32
餐饮服务X₅	餐饮服务设施POI数量	24.08	41.51
公司企业X₆	公司企业POI数量	23.85	40.70
购物服务X₇	购物服务设施POI数量	67.51	119.56
金融服务X₈	金融服务设施POI数量	3.04	7.17
科教服务X₉	科教文化服务设施POI数量	15.48	25.57
生活服务X₁₀	生活服务设施POI数量	68.14	117.94
休闲服务X₁₁	休闲服务设施POI数量	9.31	16.78
医疗服务X₁₂	医疗机构设施POI数量	8.90	14.93
政府机构X₁₃	政府单位POI数量	11.55	17.36
住宿服务X₁₄	酒店住宿设施POI数量	3.45	9.04
商务住宅X₁₅	小区住宅POI数量	8.69	18.44
风景名胜X₁₆	景点服务设施POI数量	0.93	2.76
公共交通指标
地面公交X₁₇	公交站点数量	4.63	4.48
地铁X₁₈	地铁站点数量	0.65	1.91

变量	长距离网约车	短距离网约车	空间自相关			VIF
变量	回归系数	回归系数	Moran's I	Z值	P值	VIF
LDT			0.452	193.613	0.000
SDT			0.376	161.972	0.000
主干路	0.063^***	0.057^***	0.102	43.361	0.000	1.112
人口分布	0.200^***	0.164^***	0.359	156.490	0.000	1.441
公司企业	0.103^***	0.093^***	0.201	86.061	0.000	1.601
购物服务	0.253^***	0.190^***	0.205	88.196	0.000	2.325
休闲服务	0.266^***	0.264^***	0.255	108.842	0.000	2.077
医疗服务	-0.115^***	-0.160^***	0.103	44.025	0.000	1.622
商务住宅	0.256^***	0.465^***	0.323	137.649	0.000	2.279
地面公交	-0.052^***	-0.250^***	0.297	125.970	0.000	2.167

模型	长距离网约车出行需求（LDT）				短距离网约车需求（SDT）
模型	AIC_C	R²	R²_Adj	带宽	AIC_C	R²	R²_Adj	带宽
OLS	3 344.308	0.602	0.600	1 734	3 540.129	0.554	0.552	1 734
GWR	1 311.593	0.936	0.914	75	1 250.937	0.938	0.917	75
MGWR	627.878	0.953	0.939	［61，417］	-312.400	0.974	0.966	［47，1 733］

变量		平均值	标准差	最小值	中位数	最大值	带宽
LDT	常数项	-0.118	0.240	-0.332	-0.217	0.824	61
	主干路	0.019	0.069	-0.118	0.002	0.536	61
	人口分布	0.078	0.088	-0.129	0.069	0.719	97
	公司企业	0.008	0.069	-0.213	0.001	0.399	61
	购物服务	0.038	0.111	-0.139	-0.002	0.496	409
	休闲服务	0.114	0.145	-0.029	0.046	0.746	61
	医疗服务	0.054	0.035	0.007	0.040	0.154	417
	商务住宅	0.030	0.088	-0.204	0.010	0.472	61
	地面公交	0.059	0.088	-0.039	0.025	0.479	68
SDT	常数项	-0.143	0.165	-0.236	-0.205	0.760	61
	主干路	0.013	0.055	-0.060	0.000	0.499	59
	人口分布	0.024	0.052	-0.098	0.005	0.322	61
	公司企业	0.005	0.050	-0.180	0.001	0.359	61
	购物服务	0.018	0.070	-0.196	0.003	0.483	47
	休闲服务	0.053	0.111	-0.011	0.005	0.580	61
	医疗服务	0.004	0.037	-0.073	-0.001	0.241	54
	商务住宅	0.049	0.109	-0.060	0.004	0.573	47
	地面公交	-0.006	0.000	-0.007	-0.006	-0.005	1 733

Multi-scale spatial heterogeneity analysis of influencing factors of ride-hailing travel demand

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