自动驾驶公众接受度研究综述

唐立; 卿三东; 徐志刚; 周厚庆

doi:10.19818/j.cnki.1671-1637.2020.02.011

自动驾驶公众接受度研究综述

doi: 10.19818/j.cnki.1671-1637.2020.02.011

1.
西华大学汽车与交通学院, 四川成都 610039
2.
长安大学信息工程学院, 陕西西安 710064

基金项目:

国家重点研发计划项目 2019YFB1600100

国家自然科学基金项目 61973045

陕西省重点研发计划项目 2018ZDXM-GY-013

四川省教育厅科研项目 18ZB0565

详细信息

作者简介:
唐立(1988-), 女, 四川遂宁人, 西华大学副教授, 工学博士, 从事交通行为理论研究

中图分类号: U491.1
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出版历程
- 收稿日期: 2019-11-10
- 刊出日期: 2020-04-25

Research review on public acceptance of autonomous driving

1.
School of Automobile and Transportation, Xihua University, Chengdu 610039, Sichuan, China
2.
School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

National Key Research and Development Program of China 2019YFB1600100

National Natural Science Foundation of China 61973045

Key Research and Development Project of Shaanxi Province 2018ZDXM-GY-013

Scientific Research Project of the Education Department of Sichuan Province 18ZB0565

More Information

Author Bio:
TANG Li(1988-), female, associateprofessor, PhD, E-mail: tangli@mail.xhu.edu.cn

摘要

摘要: 全面梳理并总结了自动驾驶公众接受度领域的相关研究, 从接受自动驾驶的可能性与态度、了解与信任程度、感知与关注点、支付意愿和使用偏好5个方面定义并阐述了接受度的内涵; 从调查对象的选取、问卷设计、调查方式与抽样、模型构建与数据分析方法等方面对比了现有研究采用的数据采集和分析方法; 总结了影响自动驾驶公众接受度的关键因素, 剖析了其对公众接受度的影响, 指出了存在的问题和未来研究方向。研究结果表明: 现有大部分研究重点关注接受自动驾驶的可能性、态度和使用偏好等问题, 对支付意愿的研究相对较少; 公众对自动驾驶普遍持积极态度, 对自动驾驶技术及其相关功能有所了解; 安全问题是人们对自动驾驶的首要关注点, 不同群体对该问题的担忧程度有显著差异; 人们为享受自动驾驶技术而愿意支付额外费用的意愿不够强烈, 来自发达国家受访者的支付意愿普遍低于发展中国家受访者; 个人心理和生理属性, 社会人口属性, 伦理、法律责任和车辆安全水平, 车辆自动化水平及相关属性, 出行相关属性以及环境因素等是影响公众对自动驾驶接受度的几类关键因素; 然而, 现有研究对伦理和法律责任等因素的量化分析还较为缺乏, 性别、年龄和收入水平等部分关键因素的影响仍存在争议, 还需进一步讨论; 相关研究在对样本的代表性分析、问卷和调查方案的精细化设计以及关键因素的具体作用机制分析等方面还有待进一步深入。
- 智能交通 /
- 自动驾驶 /
- 公众接受度 /
- 关键因素 /
- 支付意愿 /
- 调查设计
Abstract: The relevant studies in the field of public acceptance of autonomous driving were comprehensively sorted out and summarized. The connotation of acceptance was defined and explained from five aspects such as the possibility and attitude on accepting the autonomous driving, degrees of understanding and trust, perception and focus, willingness to pay and use preference. The data collection and analysis methods used in the existing researches were compared and analyzed from the aspects such as the survey object selection, questionnaire design, survey and sampling schemes, modelling and data analysis methods. The key factors impacting the public acceptance of autonomous driving were summarized. The influences of key factors on the public acceptance were analyzed. The problems and future research directions were pointed out. The research result indicates that most of the existing studies focus on the problems of accepting possibility of autonomous driving, attitude and use preference. The research relating to the willingness to pay is relatively rare. The public is generally positive about the autonomous driving, and have certain knowledges of autonomous driving technology and its related functions. The safety issue is people's primary concern for the autonomous driving, while the concern degrees are significantly different among various groups. People's willingness to pay extra money to enjoy the autonomous driving technology is not strong enough. The willingness to pay of respondents from developed countries is generally lower than that from developing countries. The personal psychological and physiological attributes, social demographic attribute, ethics, legal responsibility and vehicle safety level and related attributes, vehicle automation level and related attributes, travel-related attributes and environmental factor are several key factors influencing the public acceptance of autonomous driving. However, the quantitative analysis on the factors such as ethics and legal responsibility in existing researches is still lacking. The effects of some key factors such as gender, age and income level are still controversial, and further discussion is needed. In-depth research is needed in the aspects of sample representative analysis, refined design of questionnaire and survey, and analysis of specific mechanisms of key factors.
- intelligent transportation /
- autonomous driving /
- public acceptance /
- key factor /
- willingness to pay /
- survey design

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图 1 关键文献的调查时间和调查地区分布

Figure 1. Survey times and regional distributions of key literatures

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图 2 TAM结构

Figure 2. Structure of TAM

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图 3 UTAUT模型结构

Figure 3. Structure of UTAUT model

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图 4 AVAM结构

Figure 4. Structure of AVAM

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表 1 关键文献研究的接受度类型和研究对象

Table 1. Acceptance types and objects for studies of key literatures

文献编号	接受度类型					研究对象
文献编号	接受自动驾驶的可能性与态度	了解与信任程度	感知与关注点	支付意愿	使用偏好	研究对象
^[21]	√	√	√	√	√	公众(≥18岁)
^[22]	√		√		√	公众(≥18岁)
^[23]	√	√			√	公众(18~65岁)
^[24]	√	√			√	汽车用户
^[25]	√	√	√	√	√	公众(≥18岁)
^[32]					√	公众(≥18岁)
^[33]	√					公众
^[34]	√	√				公众
^[35]					√	公众
^[36]	√		√	√		公众(≥18岁)
^[37]				√	√	公众(≥18岁, 每月至少旅游2次)
^[38]	√				√	自动驾驶巴士乘客
^[39]		√				公众(母语为荷兰语, 拥有驾照)
^[40]			√	√	√	公众(≥18岁)
^[41]			√		√	汽车用户
^[42]					√	公众(≥15岁)
^[43]					√	公众
^[44]	√				√	公众
^[45]				√	√	公众(≥18岁)
^[46]	√		√	√	√	公众(≥18岁)
^[47]	√	√	√			公众
^[48]	√				√	公众
^[49]				√	√	汽车用户
^[50]	√	√	√	√	√	公众
^[51]			√		√	学生
^[52]					√	公众
^[53]	√				√	公众(20~59岁)
^[54]	√	√	√	√	√	公众
^[55]	√	√	√			公众(≥18岁)
^[56]	√				√	汽车用户
^[57]	√	√	√			公众(≥18岁)
^[58]	√				√	公众
^[59]	√		√		√	学生、教师
^[60]			√		√	公众
^[61]	√		√			公众(18~64岁)
^[62]		√				公众
^[63]	√					自动驾驶巴士乘客
^[29]	√	√	√	√	√	公众
^[64]	√	√	√			公众
^[65]					√	公众
^[66]					√	公众
^[67]				√	√	公众(≥18岁, 家庭拥车, 非出租车驾驶人)
^[68]	√		√	√	√	公众(休闲场所)
^[69]	√					公众
^[70]	√		√			成年父母(孩子年龄为0~14岁, 拥有汽车)
^[71]	√	√	√			驾驶人
^[72]	√	√		√	√	公众
^[73]	√	√	√			公众
^[74]				√	√	汽车用户
^[75]	√	√			√	公众(18~73岁)
^[76]	√		√			公众
^[77]	√	√	√			学生
^[78]	√		√			公众(持有驾照)
^[79]	√	√	√		√	公众(包括残疾人)
^[80]			√			本科学生
^[81]	√	√	√		√	公众(≥16岁)
^[82]				√	√	汽车爱好者
^[83]	√	√				智力障碍患者
^[84]	√					公众
^[85]	√	√	√			公众(听说过自动驾驶)
^[86]	√		√			公众
^[87]		√	√	√		公众
^[88]		√	√		√	公众
^[89]			√		√	汽车制造商员工

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表 2 问卷问题设置形式及数量

Table 2. Formats and numbers of questions in questionnaires

项目	类别	频率%	数值
问题设置形式	量表	76	49
	选择试验	13	8
	开放式问题及其他	11	7
量表问卷问题数	< 20	22	11
	[20, 40)	48	23
	[40, 60)	20	10
	[60, 80)	8	4
	≥80	2	1
	最小/最大值		12/94
	平均值		34
	中位数		30
选择试验	选择任务数(平均数/中位数)		6/6
	选项数(平均数/中位数)		4/4
	属性数(平均数/中位数)		5/6
	属性水平数(平均数/中位数)		3/3

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