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

Zhongxiang Feng, Jingyu Li, Xiaoqin Xu, Amy Guo, Congjun Huang and Xu Jiang
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Zhongxiang Feng: School of Transportation, Southeast University, Nanjing 210096, China
Jingyu Li: School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, China
Xiaoqin Xu: School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China
Amy Guo: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
Congjun Huang: Hefei Urban Planning and Design Institute, Hefei 230009, China
Xu Jiang: Hefei Urban Planning and Design Institute, Hefei 230009, China

IJERPH, 2021, vol. 18, issue 21, 1-16

Abstract: 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.

Keywords: drivers; automated driving; take-over intention; technology acceptance; self-efficacy; risk perception (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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