考虑停车可用性的建成环境对小汽车通勤出行的影响

doi:10.13229/j.cnki.jdxbgxb20180047

Abstract

Abstract:

In order to examine the influence of built environment and parking availability on commuting mode choice, the integrated path analysis?discrete choice model (PAM?DCM) is proposed. In this model the car ownership and commuting distance are considered as the mediating variables. The data from Changchun household travel survey is used to estimate model parameters using Mplus software. The results indicate that the model considering parking availability performs better than the model ignoring the parking availability. Also, the influence of parking availability on car use for commuting is significantly positive. Meanwhile, built environment in residence and workplace has significant effects on car use for commuting. Moreover, it is found that the influence of residential built environment is greater than that in workplace.

Key words: engineering of communications and transportation system, parking availability, built environment, car commuting, integrated path analysis?discrete choice model (PAM?DCM)

CLC Number:

U491

Chao⁃ying YIN,Chun⁃fu SHAO,Xiao⁃quan WANG. Influence of urban built environment on car commuting considering parking availability[J].Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 714-719.

Figures/Tables 6

Table 1

Fig.1

Fig.2

Table 2

Fitting effects of models"

拟合指标	模型1	模型2	参考值
$χ 2$	5.984	5.580	χ²值越小表示偏差越小，模型拟合越好
CFI	0.994	0.999	>0.90
TLI	0.949	0.955	>0.90
RMSEA	0.015	0.015	<0.05

Table 2

Table 3

Table 4

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变量名称		变量描述	均值	标准差
社会经济属性	性别	男为1；女为0	0.54	0.50
	年龄/岁	连续变量	38.16	10.74
	教育程度	大学及以上学历为1；大学以下学历为0	0.35	0.48
家庭属性	家庭规模/人	连续变量	2.99	0.875
	家庭年平均收入/万元	家庭年平均收入≤2万元为1；家庭年平均收入为> 2万元且≤10万元为2；家庭年平均收入>10万元为3	2.10	0.390
	家庭小汽车拥有	拥有小汽车为1；否则为0	0.24	0.430
建成环境	土地利用混合度	衡量“多样性”维度	0.59	0.17
	公共交通站点密度	衡量“公交设施可达性”维度	10.50	5.91
	到CBD的距离	衡量“目的地可达性”维度	4.80	2.91
	交叉口密度	衡量“设计”维度	33.38	33.83
停车可用性	交通小区停车场密度	衡量停车可用性	70.37	80.52
停车可用性	500 m范围内停车可用性	居住地或工作地500m范围内有停车场为1；否则为0	0.41	0.52
出行属性	通勤距离	连续变量	6.68	11.74
出行属性	通勤方式	使用小汽车通勤为1；否则为0	0.13	0.34

变量名称		直接效应		间接效应		总效应
变量名称		参数估计	t统计量	参数估计	t统计量	参数估计	t统计量
社会经济属性	性别	0.504	23.675**	0.090	4.550**	0.594	24.226**
	年龄	0.106	10.747**	0.040	4.268**	0.146	13.808**
	教育程度	0.098	4.296**	0.698	30.319**	0.796	32.733**
家庭属性	家庭规模	0.005	0.471	0.031	1.974**	0.036	2.403**
家庭属性	家庭收入	0.003	0.131	0.023	2.106**	0.026	1.997**
居住地建成环境	居住地土地利用混合度	-0.148	-1.962**	-0.918	-6.154**	-1.066	-4.052**
	居住地公共交通站点密度	-0.004	-1.912*	-0.016	-2.104**	-0.020	-2.826**
	居住地到CBD的距离	0.117	1.793*	0.026	3.025**	0.143	3.723**
	居住地交叉口密度	0.000	0.232	-0.011	-2.521**	-0.011	-2.002**
工作地建成环境	工作地土地利用混合度	-0.140	-0.915	-0.398	-2.058**	-0.538	-1.864*
	工作地公共交通站点密度	0.000	0.177	-0.011	-1.775*	-0.011	-2.448**
	工作地到CBD的距离	0.041	0.373	0.018	2.722**	0.059	2.733**
	工作地交叉口密度	0.000	0.982	-0.001	1.298	-0.001	0.662

变量名称		直接效应		间接效应		总效应
变量名称		参数估计	t统计量	参数估计	t统计量	参数估计	t统计量
社会经济属性	性别	0.505	23.774**	0.094	4.772**	0.598	24.330**
	年龄	0.106	10.809**	0.040	4.255**	0.146	13.783**
	教育程度	0.098	4.506**	0.690	30.877**	0.788	32.457**
家庭属性	家庭规模	0.005	0.504	0.030	3.954**	0.035	4.006**
家庭属性	家庭收入	0.004	0.152	0.007	2.256**	0.011	2.088**
居住地建成环境	居住地土地利用混合度	-0.120	-1.989**	-0.832	-5.490**	-0.952	-3.693**
	居住地公共交通站点密度	-0.003	-1.798*	-0.014	-2.590**	-0.017	-2.906**
	居住地到CBD的距离	0.105	1.966**	0.023	4.200**	0.128	4.452**
	居住地交叉口密度	0.001	1.190	-0.014	-4.913**	-0.013	-2.932**
工作地建成环境	工作地土地利用混合度	-0.139	-0.898	-0.322	-2.226**	-0.416	-1.982**
	工作地公共交通站点密度	0.000	-0.039	-0.010	-2.216**	-0.010	-1.746*
	工作地到CBD的距离	0.040	5.501**	0.014	2.971**	0.055	2.863**
	工作地交叉口密度	0.000	0.262	-0.001	-1.287	-0.001	-0.832
停车可用性	居住地停车场密度	0.023	4.385**	0.002	5.385**	0.025	3.152**
	工作地停车场密度	0.013	3.655**	0.001	3.655**	0.014	3.231**
	居住地500 m范围内停车可用性	0.147	13.774**	0.030	3.436**	0.177	10.327**
	工作地500 m范围内停车可用性	0.113	11.226**	0.035	3.775**	0.148	12.783**

Influence of urban built environment on car commuting considering parking availability

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