Studying Driver’s Perception Arousal and Takeover Performance in Autonomous Driving

Qiuhong Wang, Haolin Chen, Jianguo Gong, Xiaohua Zhao and Zhenlong Li ()
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Qiuhong Wang: Research Institute for Road Safety of MPS, No. 3 Chongwenmenwai Street, Beijing 100062, China
Haolin Chen: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Jianguo Gong: Research Institute for Road Safety of MPS, No. 3 Chongwenmenwai Street, Beijing 100062, China
Xiaohua Zhao: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Zhenlong Li: Beijing Engineering Research Center of Urban Transport Operation Guarantee, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China

Sustainability, 2022, vol. 15, issue 1, 1-15

Abstract: The driver’s perception level and takeover performance are two major factors that result in accidents in autonomous vehicles. This study’s goal is to analyze the change in drivers’ perception level and its influence on takeover performance during autonomous driving. A takeover behavior test platform is implemented based on a high-fidelity driving simulator. The fog zone is selected as the takeover scenario. Thus, a 2 (takeover request time: 5 s, 10 s) by 2 (non-driving-related task: work task, entertainment task) takeover experiment was conducted. A generalized linear mixed model is developed to explore the influence of the perception level on takeover performance. The study finds out that, after the takeover request is triggered, the driver’s gaze duration is shortened and the pupil area is enlarged, which is helpful for the driver to extract and understand the road information faster. Male drivers have greater perception levels than female drivers, and they prioritize leisure tasks more than professional ones. The drivers’ perception level decreases when age increases. The shorter the gaze duration is, and the larger the pupil area is, the shorter the takeover response time will be. In addition, drivers’ perception level has a positive effect on takeover performance. Finally, this study provides a reference for revealing the changing rules of drivers’ perception level in autonomous driving, and the study can provide support for the diagnosis of takeover risks of autonomous vehicles from the perspective of human factors.

Keywords: autonomous vehicles; perception level; takeover performance; generalized linear mixed model; driving simulator (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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