Influence Characteristics of Automated Driving Takeover Behavior in Different Scenarios

被引：0
|
作者：
Zhao X.-H. [1 ,2 ]
Chen H.-L. [1 ,2 ]
Li Z.-L. [1 ,2 ]
Li H.-J. [1 ,2 ]
Gong J.-G. [3 ]
Fu Q. [1 ,2 ]
机构：
[1] Beijing Engineering Research Center of Urban Transportation Operation Guarantee, Beijing University of Technology, Beijing
[2] College of Metropolitan Transportation, Beijing University of Technology, Beijing
[3] Road Traffic Safety Research Center of the Ministry of Public Security, Beijing
来源：
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | 2022年 / 35卷 / 09期
基金：
中国国家自然科学基金;
关键词：
automated driving; driving simulation technology; generalized linear mixed model; influence factor; takeover behavior; traffic engineering;
D O I：
10.19721/j.cnki.1001-7372.2022.09.015
中图分类号：
学科分类号：
摘要：
To explore the influence characteristics of automated driving takeover behavior in different scenarios. For drivers, automated vehicle and traffic environment, this study proposes a research framework for the automated driving test. Based on the driving simulation technology, an automated driving test platform was developed, and cases verified that this test platform can provide effective support for automated driving related technology tests. This study designed 18 freeways takeover scenarios with design elements of takeover request time, non-driving-task, scenarios, traffic flow and carried out driving simulation experiments to explore the adaptability differences of drivers from the subjective aspects. And from the objective aspect, the generalized linear mixed model was constructed to explore the influence of driver attribute factors (gender, age, driving age) and takeover situation factors (takeover scenario, takeover request time, no-driving-related task) and their interaction on takeover behavior. Statistical analysis results show that: ① There are statistical differences between male and female in trust and state perception of automated driving technology. Males have higher adaptability to automated driving technology than females. ② The driver's age and driving age have significant influence on the technology acceptance before and after the experiment, and there are statistical differences in the technology trust and state perception. Middle-aged people and elderly people, as well as people of middle and high driving age, have relatively high adaptability. ③ Different levels of factors lead to different takeover success ratio, takeover correct ratio and first control behavior. The generalized linear mixed model results show that: ① Takeover situation factors and their interaction have significant influence on takeover behavior indicators. ② There is an interaction between the driver attribute factor and the takeover scenario factor in the model. The study is based on driving simulation technology to develop an automated driving test platform, which is worth promoting. Besides, the study results can lay a foundation for further exploring the influencing mechanism of automated driving takeover behavior. © 2022 Xi'an Highway University. All rights reserved.
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页码：195 / 214
页数：19
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