Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors

Drivers’ take-over intention is important for the design of the automated driving systems and affects the safety of automated driving. This study explored the influence factors on drivers’ take-over intention during conditionally automated driving, examined the correlations among factors through pat...

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Autores principales:	Zhongxiang Feng, Jingyu Li, Xiaoqin Xu, Amy Guo, Congjun Huang, Xu Jiang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	drivers automated driving take-over intention technology acceptance self-efficacy risk perception Medicine R
Acceso en línea:	https://doaj.org/article/d381e19cb0bb43c29a7405eadba71f9b
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id	oai:doaj.org-article:d381e19cb0bb43c29a7405eadba71f9b
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spelling	oai:doaj.org-article:d381e19cb0bb43c29a7405eadba71f9b2021-11-11T16:13:23ZTake-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors10.3390/ijerph1821110761660-46011661-7827https://doaj.org/article/d381e19cb0bb43c29a7405eadba71f9b2021-10-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/21/11076https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601Drivers’ take-over intention is important for the design of the automated driving systems and affects the safety of automated driving. This study explored the influence factors on drivers’ take-over intention during conditionally automated driving, examined the correlations among factors through path analysis, and established a take-over intention model. A questionnaire survey was conducted in Hefei, China, and a sample of 277 drivers was obtained. Our study shows that the average take-over intention of those aged under 20 is lower than that of the older age groups. In the positive emotions (PE) scenarios, the take-over intention of aged 31–40 is significantly higher than that of the other age groups. Education and occupation have a significant influence on the take-over intention. The perceived ease of use (PEofU) and perceived usefulness (PU) of automated driving are significantly negatively correlated with drivers’ take-over intention in the road conditions (RC) and climate conditions (CC) scenarios. In addition, through path model analysis, our study shows that trust in the safety of autonomous vehicles (AVs) plays an important role in drivers’ take-over intention. Technology acceptance, risk perception and self-efficacy has indirectly correlated with take-over intention through trust in the safety of AVs. In general, drivers with lower technology acceptance, lower self-efficacy and higher risk perception are less likely to trust automated driving technology and have shown stronger intention to take-over the control of the vehicles.Zhongxiang FengJingyu LiXiaoqin XuAmy GuoCongjun HuangXu JiangMDPI AGarticledriversautomated drivingtake-over intentiontechnology acceptanceself-efficacyrisk perceptionMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11076, p 11076 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	drivers automated driving take-over intention technology acceptance self-efficacy risk perception Medicine R
spellingShingle	drivers automated driving take-over intention technology acceptance self-efficacy risk perception Medicine R Zhongxiang Feng Jingyu Li Xiaoqin Xu Amy Guo Congjun Huang Xu Jiang Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
description	Drivers’ take-over intention is important for the design of the automated driving systems and affects the safety of automated driving. This study explored the influence factors on drivers’ take-over intention during conditionally automated driving, examined the correlations among factors through path analysis, and established a take-over intention model. A questionnaire survey was conducted in Hefei, China, and a sample of 277 drivers was obtained. Our study shows that the average take-over intention of those aged under 20 is lower than that of the older age groups. In the positive emotions (PE) scenarios, the take-over intention of aged 31–40 is significantly higher than that of the other age groups. Education and occupation have a significant influence on the take-over intention. The perceived ease of use (PEofU) and perceived usefulness (PU) of automated driving are significantly negatively correlated with drivers’ take-over intention in the road conditions (RC) and climate conditions (CC) scenarios. In addition, through path model analysis, our study shows that trust in the safety of autonomous vehicles (AVs) plays an important role in drivers’ take-over intention. Technology acceptance, risk perception and self-efficacy has indirectly correlated with take-over intention through trust in the safety of AVs. In general, drivers with lower technology acceptance, lower self-efficacy and higher risk perception are less likely to trust automated driving technology and have shown stronger intention to take-over the control of the vehicles.
format	article
author	Zhongxiang Feng Jingyu Li Xiaoqin Xu Amy Guo Congjun Huang Xu Jiang
author_facet	Zhongxiang Feng Jingyu Li Xiaoqin Xu Amy Guo Congjun Huang Xu Jiang
author_sort	Zhongxiang Feng
title	Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
title_short	Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
title_full	Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
title_fullStr	Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
title_full_unstemmed	Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
title_sort	take-over intention during conditionally automated driving in china: current situation and influencing factors
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d381e19cb0bb43c29a7405eadba71f9b
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Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors

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