共享无人驾驶汽车对地铁站接驳方式选择的影响

doi:10.13229/j.cnki.jdxbgxb.20220912

Abstract

Abstract:

In order to explore the heterogeneity of preferences of travel choice and the potential of shared autonomous vehicles to solve the last-mile connection problem of train trips， the last-mile travel mode choice of travelers based on the theory of planned behavior was analyzed. First， a latent variable model was established to obtain travelers' attitudes， subjective norms， perceived behavior control， and behavioral intentions toward autonomous vehicles. Secondly， latent psychological variables into the random parameter Logit model and conduct an empirical analysis was incorporated to study factors of the behavior of the last mile of train trip. Finally， an elasticity analysis was conducted to study the impact of travel time on the travel mode choice. The research results show that the random coefficient Logit model has higher fitness than the traditional multinomial Logit model. Travelers' preferences for travel time are heterogeneous. The travel time coefficient is not a fixed value but follows a normal distribution with a mean of -0.153 and a standard deviation of 0.520. Travelers' attitudes and perceived behavioral control towards autonomous vehicles have a significant impact on travel behavior. The probability of choosingshared autonomous vehicles increases by 0.799% with every 1% reduction in the travel time of autonomous vehicles； The probability of choosing shared autonomous vehicles increases by 1.155 % with every 1% increase in the travel time of shared bicycles.

Key words: engineering of communication and transportation system, last-mile travel, theory of planned behavior, random parameter Logit model（RPLM）, autonomous vehicles

CLC Number:

U121

Zhi-wei LIU,Zheng-yun SONG,Jian-rong LIU. Impact of shared autonomous vehicles on choice of subway station connection methods[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(12): 3424-3431.

Figures/Tables 7

Table 1

Table 2

Fig.1

Table 3

Reliability and validity test of sample"

潜变量	观测变量	Cronbach's $α$	CR	因子载荷	AVE
ATT	ATT1	0.940 0.940 0.940	0.941 0.941 0.941	0.947	0.889 0.889 0.889
	ATT2			0.949
	ATT3			0.939
SN	SN1	0.929 0.929 0.929	0.955 0.955 0.955	0.940	0.875 0.875 0.875
	SN2			0.943
	SN3			0.924
PBC	PBC1	0.872 0.872 0.872	0.922 0.922 0.922	0.851	0.797 0.797 0.797
	PBC2			0.920
	PBC3			0.905
BIU	BIU1	0.941 0.941 0.941	0.963 0.963 0.963	0.941	0.896 0.896 0.896
	BIU2			0.961
	BIU3			0.933

Table 3

Table 4

Fitness statistics of confirmatory factor analysis"

项目	$χ 2 / d f$	RMSEA	CFI	TLI	SRMR
参考值	1~3	≤0.08	≥0.900	≥0.900	<0.08
模型参数	1.335	0.06	0.983	0.977	0.024

Table 4

Table 5

Estimation results of the MNLM and RPLM"

出行方式及变量		多项Logit模型		随机系数Logit模型
出行方式及变量		系数	Z值	系数	Z值
出行时间均值		-0.018^***	-2.85	-0.153^***	-6.07
出行时间标准差		—	—	0.520^***	16.22
等待时间		-0.070^***	-5.65	-0.056^***	-4.00
出行费用		-0.133^***	-4.74	-0.287^***	-8.31
步行	性别	-0.043 21	-0.78	-0.129	-1.13
	年龄（18~30岁）	-0.002	-0.02	0.142	0.59
	年龄（31~45岁）	0.241	1.64	0.379	1.28
	年龄（46~55岁）	0.003	0.01	-0.047	-0.13
	高中及以下	0.180	1.00	0.303	0.79
	大专	-0.493^***	-3.92	-0.673^**	-2.44
	本科	0.172^*	1.68	0.326	1.52
	公务员、事业单位人员	-0.081	-0.71	-0.078	-0.33
	企业员工	-0.513^***	-4.24	-0.479^*	-1.87
	自由职业	-0.154	-1.05	-1.033^***	-3.42
	家庭月收入（5000元以下）	-0.286^***	-3.19	-0.244	-1.32
	家庭月收入（5000~10 000元）	-0.075	-0.80	0.242	1.28
	家庭月收入（10 000~20 000元）	-0.129	-1.14	-0.041	-0.18
	是否有学龄儿童	-0.169^***	-2.94	-0.149	-1.27
	是否有驾照	-0.009	-0.14	0.134	1.08
	是否有小汽车	0.028	0.47	0.199	1.61
	家庭人口数	0.068*	1.94	-0.056	-0.88
共享自行车	性别	0.078	1.43	0.063	1.08
	年龄（18~30岁）	-0.043	-0.38	-0.005	-0.04
	年龄（31~45岁）	0.524^***	3.69	0.521^***	3.55
	年龄（46~55岁）	0.104	0.62	0.061	0.35
	高中及以下	0.052	0.29	0.026	0.14
	大专	-0.636^***	-5.08	-0.704^***	-5.43
	本科	0.181^*	1.79	0.219^**	2.10
	公务员、事业单位人员	-0.232^**	-2.07	-0.296^**	-2.53
	企业员工	-0.490^***	-4.20	-0.550^***	-4.56
	自由职业	0.097	0.70	-0.055	-0.39
	家庭月收入（5000元以下）	-0.380^***	-4.23	-0.445^***	-4.70
	家庭月收入（5000~10 000元）	0.036	0.39	0.066	0.67
	家庭月收入（10 000~20 000元）	0.120	1.09	0.142	1.22
	是否有学龄儿童	-0.100^*	-1.75	-0.131^**	-2.18
	是否有驾照	-0.079	-1.29	-0.026	-0.39
	是否有小汽车	0.118^**	2.04	0.142^**	2.33
	家庭人口数	0.098^***	2.96	0.147^***	4.12
共享无人驾驶汽车	性别	0.001	0.01	-0.023	-0.30
	年龄（18~30岁）	-0.505^***	-3.84	-0.667^***	-4.53
	年龄（31~45岁）	0.424^***	2.73	0.263	1.55
	年龄（46~55岁）	0.055	0.30	0.145	0.73
	高中及以下	0.500^***	2.60	0.466^**	2.18
	大专	-0.375^**	-2.54	-0.366^**	-2.23
	本科	-0.132	-1.11	-0.084	-0.64
	公务员、事业单位人员	-0.203	-1.52	-0.148	-1.00
	企业员工	-0.388^***	-2.82	-0.175	-1.16
	自由职业	0.101	0.63	0.136	0.76
	家庭月收入（5000元以下）	-0.596^***	-5.42	-0.550^***	-4.50
	家庭月收入（5000~10 000元）	-0.281^**	-2.47	-0.237^*	-1.86
	家庭月收入（10 000~20 000元）	-0.187	-1.41	-0.145	-0.98
	是否有学龄儿童	-0.189^***	-2.74	-0.103	-1.33
	是否有驾照	-0.111	-1.50	-0.115	-1.33
	是否有小汽车	0.183^**	2.49	0.172^**	2.13
	家庭人口数	0.108^***	3.26	0.038	1.03
	ATT	0.416^***	4.31	0.410^***	3.68
	SN	0.280^***	2.99	0.206^*	1.85
	PBC	-0.102	-1.03	0.056	0.45
	BIU	0.186^**	2.22	0.128	1.27
对数似然值		-4770.407		-3894.067
伪平方值		0.063		0.308

Table 5

Table 6

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潜变量	观测变量	符号
态度	是否赞同无人驾驶汽车有利	ATT₁
	是否赞同无人驾驶汽车发展方向是积极	ATT₂
	是否赞同无人驾驶汽车值得期待	ATT₃
社会规范	亲戚朋友是否赞同我未来使用无人驾驶汽车	SN₁
	亲戚朋友希望我未来能使用无人驾驶汽车	SN₂
	朋友使用无人驾驶汽车也会影响我的决定	SN₃
感知行为控制	使用无人驾驶汽车完全由自己决定	PBC₁
	我可以承受无人驾驶汽车的出行费用	PBC₂
	是否赞同未来用无人驾驶汽车出行机会多	PBC₃
行为意向	是否赞同未来使用无人驾驶汽车	BIU₁
	是否赞同未来购买无人驾驶汽车	BIU₂
	是否赞同将无人驾驶汽车向身边亲戚朋友推荐	BIU₃

属性	属性水平	水平数量
出行距离/m	500、1000、1500	3
步行出行时间/min	-30%、-10%、+20%∥根据距离计算行程时间（出行速度为4 km/h）	3
共享自行车出行费用/元	-30%、-10%、+20%∥估计出行费用（≤30 min为1.5元，31~60 min为3元）	3
共享自行车出行时间/min	-30%、-10%、+20%∥根据距离计算行程时间（出行速度为15 km/h）	3
公交车出行费用/元	-30%、-10%、+20%∥估计出行费用（1~2元）	6
公交车出行时间/min	-30%、-10%、+20%∥根据距离计算行程时间（出行速度为18 km/h）	3
公交车等待时间/min	4、7、10	3
共享无人驾驶汽车出行费用/元	-30%、-10%、+20%∥根据距离估计出行费用（2元/500 m）	3
共享无人驾驶汽车出行时间/min	-30%、-10%、+20%∥根据距离计算行程时间（出行速度为40 km/h）	3
共享无人驾驶汽车等待时间/min	2、5、8	3

Impact of shared autonomous vehicles on choice of subway station connection methods

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